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Reading: The Rise of the Relational Model

(Subject: Database/Authored by: Liping Liu on 8/13/2025 4:00:00 AM)/Views: 12706
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The Rise of Relational Databases by National Science Foundation

Large-scale computer applications require rapid access to large amounts of data. A computerized checkout system in a supermarket must track the entire product line of the market. Airline reservation systems are used at many locations simultaneously to place passengers on numerous flights on different dates. Library computers store millions of entries and access citations from hundreds of publications. Transaction processing systems in banks and brokerage houses keep the accounts that generate international flows of capital. World Wide Web search engines scan thousands of Web pages to produce quantitative responses to queries almost instantly. Thousands of small businesses and organizations use databases to track everything from inventory and personnel to DNA sequences and pottery shards from archaeological digs.

Thus, databases not only represent significant infrastructure for computer applications, but they also process the transactions and exchanges that drive the U.S. economy. A significant and growing segment of the software industry, known as the database industry, generates about $8 billion in annual revenue. U.S. companies--including IBM Corporation, Oracle Corporation, Informix Corporation, Sybase Incorporated, Teradata Corporation (now owned by NCR Corporation), and Microsoft Corporation--dominate the world market. This dominance stems from a serendipitous combination of industrial research, government-funded academic work, and commercial competition.

Much of today's market consists of relational databases based on the model proposed in the late 1960s and early 1970s. This chapter provides background on early data management systems and then examines the emergence of the relational model and its rise to dominance in the database field, and the translation of this model into successful commercial products. The final section summarizes the lessons to be learned from history. It highlights the critical role of the government in advancing this technology. For instance, although the relational model was originally proposed and developed at IBM, it was a government-funded effort at the University of California at Berkeley (UC- Berkeley) that disseminated the idea widely and gave it the intellectual legitimacy required for broad acceptance and commercialization.

This case study does not address the entire database field (it omits topics such as transaction processing, distributed databases, and multimedia), but rather focuses on events that illustrate the ways in which synergistic interactions of government, universities, and industry built U.S. leadership in a particular subfield, largely through the work of individuals who developed and then transferred technology between firms and laboratories. As James Gray, a senior database researcher, has observed: "A very modest federal research investment, complemented by an also- modest industrial research investment, led directly to U.S. dominance of this market" (CSTB, 1995a).

 

BACKGROUND

Emergence of Computerized Databases

The U.S. government has always had significant requirements for the collection, sorting, and reporting of large volumes of data. In 1890, the Bureau of the Census encouraged a former employee, Herman Hollerith, to develop the world's first automated information processing equipment. The resulting punched-card machines processed the censuses of 1890 and of 1900. In 1911, Hollerith's company merged with another, also founded with Census support; the resulting company soon became known as International Business Machines (Anderson, 1988), now IBM.

During World War I, the government used new punched-card technology to process the various data sets required to control industrial production, collect the new income tax, and classify draftees. The Social Security Act of 1935 made it necessary to keep continuous records on the employment of 26 million individuals. For this, "the world's biggest bookkeeping job," IBM developed special collating equipment. The Census Bureau purchased the first model of the first digital computer on the commercial market, the UNIVAC I (itself based on the government-funded Electronic Discrete Variable Automatic Computer (EDVAC) project at the University of Pennsylvania). In 1959, the Pentagon alone had more than 200 computers just for its business needs (e.g., tracking expenses, personnel, spare parts), with annual costs exceeding $70 million. U.S. dominance of the punched-card data processing industry, initially established with government support, was a major factor in U.S. companies' later dominance in electronic computing.

By the early 1960s, substantial progress had been made in removing hardware- specific constraints from the tasks of programmers. The term "database" emerged to capture the sense that the information stored within a computer could be conceptualized, structured, and manipulated independently of the specific machine on which it resided. Most of the earliest database applications were developed in military command and intelligence environments, but the concept was quickly adopted by commercial users (System Development Corporation, 1964; Fry and Sibley, 1974).

Early Efforts at Standardization

As computing entered the mainstream commercial market, a number of techniques emerged to facilitate data access, ensure quality, maintain privacy, and allow for managerial control of data. In 1960, the Conference on Data Systems Languages (Codasyl), set up by the U.S. Department of Defense (DOD) to standardize software applications, established the common business-oriented language (COBOL) for programming (ACM Sigplan, 1978), incorporating a number of prior data-definition languages (Fry and Sibley, 1974). Magnetic disk drives, which could access data at random, began to replace magnetic tape drives, which required serial data access, for online storage. In 1961, Charles Bachman at General Electric Company introduced the integrated data store (IDS) system, a pioneering database management system that took advantage of the new storage technology and included novel schemas and logging, among other features.

During these early years, innovations in the practice-oriented field tended to be made by user groups and industrial researchers, with little academic involvement (CSTB, 1982; Wiederhold, 1984). In the mid-1960s, Bachman and others, largely from industry and manufacturing, set up the Database Task Group (DBTG) under Codasyl to bring some unity to the varied field (Olle, 1978). The group published a set of specifications for how computer languages, COBOL in particular, might navigate databases. In 1971, it published a formal standard, known colloquially in the industry as the Codasyl approach to database management. A number of Codasyl-based products were introduced for mainframe computers by Eckert- Mauchly Computer Corporation (the maker of Univac), Honeywell Incorporated, and Siemens AG, and, for minicomputers, by Digital Equipment Corporation (DEC) and Prime Computer Corporation.1

Notably missing from the list of vendors that supported Codasyl products was IBM, which had earlier (in 1968) introduced its own product, IMS, derived in part from a National Aeronautics and Space Administration (NASA) Apollo project. It ran on System/360 equipment. Whereas Codasyl was based on a network model of data, IBM's database used a hierarchical structure. (Cullinet Corporation provided a Codasyl-compatible database for IBM users.) Both the IBM and the Codasyl products were sometimes called navigational databases because they required the user to program or navigate around a data set. Bachman's Turing Award lecture in 1973, in fact, was entitled "The Programmer as Navigator" (Bachman, 1973; Cardenas, 1979).

EMERGENCE OF THE RELATIONAL MODEL Codd's Vision

At least one researcher at IBM was dissatisfied with both the Codasyl products and IBM's database package. Edgar F. (Ted) Codd, an Oxford-trained mathematician, joined IBM in 1949 and later moved to IBM San Jose. Codd found existing and new database technologies "taking the old-line view that the burden of finding information should be placed on users. . . . [In this view, the database management system] should only recognize simple commands and it would be up to the users to put together appropriate commands for finding what was needed" (Codd, 1982).2

In a series of IBM technical reports and then a landmark paper, "A Relational Model of Data for Large Shared Data Banks," Codd laid out a new way to organize and access data. What Codd called the "relational model" rested on two key points:

It provides a means of describing data with its natural structure only- -that is, without superimposing any additional structure for machine representation purposes. Accordingly, it provides a basis for a high level data language which will yield maximal independence between programs on the one hand and machine representation on the other. (Codd, 1970)

In other words, the relational model consisted of (1) data independence from hardware and storage implementation and (2) automatic navigation, or a high- level, nonprocedural language for accessing data. Instead of processing one record at a time, a programmer could use the language to specify single operations that would be performed across the entire data set. Codd's model had an immediate impact on research and, as described below, spawned a number of significant prototyping projects.

Given its eventual commercial success, the relational model might seem bound to emerge and even dominate the field without any government involvement in research. It was formulated, after all, entirely within the walls of an industrial laboratory. But Codd's model was long seen as something of an intellectual curiosity. To gain legitimacy within the field, it had to survive at least two battles--one in the technical community at large, and one within IBM. The relational model might not have survived either battle without government intervention, which, in this case, involved funding of a competing project at another institution.

Within IBM, the trouble was the existing database product, IMS. The company had already invested, both financially and organizationally, in the infrastructure and expertise required to sell and support it. A radical new technology had a great deal to prove before it could displace a successful, reliable, revenue-generating product such as IMS. Initially, the threat was minimal; Codd published his original paper in the open literature because no one at IBM (himself included) recognized its eventual impact. The response to this publication from the outside technical community, however, soon showed the company that the idea had great commercial potential. To head off this eventuality, IBM quickly declared IMS its sole strategic product, thus setting up Codd and his work to be criticized as counter to company goals. Internal politics further compounded the situation, as IBM was not accustomed to major software innovations coming from IBM San Jose, which until then had worked primarily on disk storage.

In spite of IBM's reaction, Codd spoke out zealously and promoted the virtues of the relational model to computer scientists. He arranged a public debate between himself and Charles Bachman, at that time the key proponent of the Codasyl- sponsored standard. The debate exposed Codd to criticism from within IBM that he was undermining the company's existing products, but it also achieved his intended effect on the technical community. In the early 1970s, two projects emerged to develop relational technology and prove its utility in practical applications. One, System R, began within IBM, and the other, Ingres, began at UC-Berkeley with military and National Science Foundation (NSF) funding. The synergy between the two projects, which were at once mutually reinforcing and competing, demonstrates the subtle but significant effects that government- supported research can have on computer technology.

System R

In the early 1970s, a group of IBM programmers moved from Yorktown to San Jose.3 The group designed and built a prototype system to demonstrate relational ideas. Dubbed System R, this prototype was intended to provide a high-level, nonnavigational, data-independent interface to many users simultaneously, with high integrity and robustness (Astrahan et al., 1976). The first phase of the project, in 1974-1975, produced a quick prototype to demonstrate feasibility, but its code was eventually abandoned. The next phase produced a full-function, multiuser version, which was evaluated in subsequent trials in 1978-1979. Perhaps the most lasting development to come out of the project was the Structured Query Language (SQL), now a U.S. and international standard for database access (Chamberlin et al., 1981; McJones, 1995).4

On its own, System R did not convince IBM management to abandon its existing product and replace it with relational databases. IBM and its customers still had strong vested interests in the established IMS technology. It took outside efforts, funded by the government, to prove that relational databases could become viable commercial products.

Ingres

In 1973, about when System R was getting started at IBM, two scientists at UC- Berkeley, Michael Stonebraker and Eugene Wong, became interested in relational databases. Initially, they raised money to design a geographic data system for Berkeley's economics group (the name Ingres, which stood for interactive graphics and retrieval system, reflects this legacy). In search of further support, Stonebraker approached the Defense Advanced Research Projects Agency (DARPA), the obvious funding source for computing research and development. Both DARPA and the Office of Naval Research (ONR) turned Ingres down, however; they were already supporting database research elsewhere.

Stonebraker then introduced his idea to other agencies, and, with help from Wong and Berkeley colleague Lotfi Zadeh, he eventually obtained modest support from the NSF and three military agencies: the Air Force Office of Scientific Research, the Army Research Office, and the Navy Electronic Systems Command. The experience of acquiring support for Ingres illustrates the importance of maintaining diverse funding sources within the government. When a researcher can propose a new idea to several potential supporters, it not only increases the chances of funding a good idea but also provides a crucial learning process as proposals are rewritten and resubmitted.

Thus funded, Ingres was developed, during the mid-1970s, into a prototype relational database system that was similar to IBM's System R but based on different hardware and a different operating system. Ingres went through an evolution similar to that of System R, with an early phase demonstrating an initial solution in 1974 followed by significant revisions to make the code maintainable. Ingres was then disseminated to a small user community, both inside and outside academia, which provided feedback to the development group. The dissemination process was advanced by the proliferation of inexpensive DEC machines in universities. Members of the project team rewrote the Ingres prototype repeatedly during these years to incorporate accumulated experience, feedback from users, and new ideas. Ingres also included its own query language, QUEL, which was similar to, but still distinct from, IBM's SQL (Stonebraker, 1976, 1980).5

DIFFUSION AND COMMERCIALIZATION OF RELATIONAL DATABASES

Ingres technology diffused into the commercial sector through three major channels: code, people, and publications. Unlike the technical details of the IBM project, Ingres source code was publicly available, and about 1,000 copies were distributed around the world so that computer scientists and programmers could experiment with the system and adjust it to their own needs. Michael Stonebraker founded Ingres Corporation (purchased by Computer Associates in 1994) to commercialize the Berkeley code directly. Robert Epstein, the chief programmer at Ingres in the 1970s, went on to co-found Britton-Lee Incorporated and then Sybase. Both Britton-Lee and Sybase used ideas and experience from the original Ingres, and government agencies were early customers of both companies. Computer Associates released a commercial version of the Ingres code in the 1980s.

Continued movement of Ingres researchers throughout the database community spread the technology even farther. Jerry Held and Carol Youseffi moved from UC-Berkeley to Tandem Computers Incorporated, where they built a relational system, the predecessor to NonStop SQL. Until joining Kleiner, Perkins, Caufield & Byers in 1998, Held was senior vice-president of engineering at Oracle, where he headed that company's database efforts. Paula Hawthorn moved from Ingres to Britton-Lee (as did Michael Ubell) and eventually became a co-founder of Illustra Information Technologies Incorporated, now part of Informix. Stonebraker himself worked with Ingres Corporation, Illustra, and Informix. Other Ingres alumni went to AT&T, Hewlett-Packard Company (HP), IBM, and Oracle, bringing with them the lessons learned from Ingres. As Robert Epstein observed, "What came from Ingres was the experience of having built a

prototype . . . to say what parts need to be done differently."6

The Ingres and System R development groups had a complex relationship that fostered a spirit of competition, as both groups worked on similar new technology. Both groups were relatively small and close-knit. Between 1973 and 1979, approximately 30 individuals cycled through the Ingres group, which never contained more than five or six programmers. The System R group included roughly 15 persons who wrote code and papers on System R and later worked with IBM's product development groups to commercialize the technology. Several members of the IBM group had Berkeley connections, and UC-Berkeley sent summer students to IBM. Timely publication and proper allocation of credit for new ideas became paramount concerns (McJones, 1995). Ingres's QUEL was in competition with IBM's SQL as a query language; the latter eventually won out and became the industry standard.

The success of SQL transpired almost in spite of IBM, which could have taken  advantage of its query language several years sooner than it did. Oracle, founded by Larry Ellison, developed and began selling an SQL-compatible product even before IBM had an SQL product in the market. Ellison had learned of SQL through publications by the System R project team. IBM was compelled to develop its SQL/DS system by the threat of competing products from other established database companies, such as Software AG, a German company. Other fledgling companies, such as Informix and Ingres, also introduced relational systems, with Informix embracing the SQL model. System R programmers influenced the industry personally as well as by their writing.7

System R and Ingres were not the only relational database efforts to spring from Codd's work. Other research at the University of Toronto, IBM in the United Kingdom, the University of Utah, and the University of Wisconsin made contributions as well. It also became clear that the relational model has limitations, particularly in handling complex data. In 1982, the Ingres project ended, and in 1985 it was transformed into Postgres at UC-Berkeley, which sought to extend the relational model to objects. This change coincided with DARPA hiring its first program manager for databases, who funded Postgres. This project became a component of the digital library and scientific database efforts within the University of California system.

A landmark year for the relational model was 1980, when IBM's SQL/DS product hit the market for mainframes, smaller vendors began selling second- generation relational systems with great commercial success, and Codd was awarded the Association for Computing Machinery's (ACM) Turing Award. The relational model had come of age.

Today, relational databases are but one way of accessing the multiple types of information computers can handle. Related research in information retrieval, multimedia, scientific databases, and digital libraries is under way, supported by DARPA, NSF, and the National Library of Medicine, among others. Still, the history of the emergence of relational database technologies, products, and companies reveals a good deal about innovation in computing and communications.

LESSONS FROM HISTORY

The federal government had important effects on the development of relational databases. The earliest days of this subfield suggest that government missions can create new markets for technology, providing incentives for innovation. The Census Bureau's need to conduct a decadal census supported the information processing industry before computers were created to automate it.

Later on, government funding hastened commercialization. An example is the case of System R and Ingres. The critical issue is not which one was more successful or influential in the long run, but rather, to paraphrase a System R team member, whether either project would have succeeded in the absence of the other. The academic interest legitimized System R within IBM, and Ingres was bootstrapped off IBM's commercial influence.8 Competitive pressure, combined  with the legitimacy bestowed on the relational model by government funding and academic interest, finally convinced IBM to sell relational database products. Were it not for the government-funded effort at UC-Berkeley, such databases probably would have been commercialized anyway, but later--and time-to-market is, of course, a critical factor with new technology.

That same example shows that the commercial interests of firms such as IBM can impede the continued development and commercialization of technologies that compete with existing product lines. IBM and its customers had vested interests in the established IMS technology and resisted change until external events proved that relational databases could become viable commercial products.

This case history also suggests that the large numbers of researchers passing through university laboratories, their willingness to share data and code, and their publication imperatives make university researchers ideal sources of technology transfer to the broader technical community. Industrial laboratories, by comparison, rarely place significant technologies directly into the public domain and have lower rates of personnel turnover, although they often benefit from greater and more stable supplies of resources. Especially in the computing industry, employees may take ideas into the marketplace on their own, but industrial laboratories are likely to publish only information that concerns completed projects or is not deemed critical to the company's vital interests.

Academic research is important for other reasons as well. Because it can push the cutting edge of technology and produce results that may evolve into commercially viable products, existing commercial suppliers never have a lock on advanced technology and are forced to respond to the marketplace of ideas.

Finally, in pursuing new ideas and new areas of technology, academic research projects can benefit from access to multiple funding sources within the government, as any individual sponsor may assess the value of a new idea from a limited perspective. Although DARPA and ONR declined to support Ingres, for example, the NSF and three other military agencies agreed to do so.

NOTES

1 For his work with IDS and the Codasyl group, Bachman was awarded the Association for Computing Machinery's A.M. Turing Award in 1973 (Bachman, 1973; King, 1983).

2 Edgar F. Codd, in an interview with a representative of the Committee on Innovation in Computing and Communications, February 7, 1997.

3 The group included Mike Blasgen, Ray Boyce, Donald Chamberlain, James Gray, Frank King, Leonard Liu, Raymond Lorie, and Franco Putzolu.

4 Donald Chamberlin, in an interview with a representative of the Committee on Innovation in Computing and Communications, February 4, 1997.

5 M. Stonebraker, in interviews with a representative of the Committee on Innovation in

http://www.nap.edu/readingroom/books/far/ch6.html 1/12/2004

Chapter 6: The Rise of Relational Databases | Funding a Revolution: Government Suppor... Page 9 of 9

Computing and Communications, December 27, 1996, and February 26, 1997.

6 Robert Epstein, in an interview with a representative of the Committee on Innovation in Computing and Communications, March 19, 1997.

7 Kapali Eswaran left IBM in the late 1970s to form his own company, and its code eventually became part of HP and Cullinet products. Jim Gray moved from IBM to Tandem, where he worked on NonStop SQL, and he is now the senior database researcher at Microsoft. Franco Putzolu also went from IBM to Tandem, where he was a principal designer of NonStop SQL, and

later went to Oracle as a senior database architect.

8 Donald Chamberlin, in an interview with a representative of the Committee on Innovation in Computing and Communications, February 4, 1997.

           Register

OOL*** posted at 9/5/2018 5:02:47 AM
Important factors for a successful framework to organize data:
a. Data redundancy avoidance
b. Easy navigation between data
c. Data retrieval should be seamless

Common features in all the logical data models:
a. Attributes used must be relevant
b. Attribute must have a single value
c. Relationship must exist between the attributes used.
Advantages and disadvantages of relational data model as opposed to other logical models?
Advantages:
a. Data can be easily modified
b. Data can be easily retrieved
c. Data redundancy is controlled
Disadvantages:
a. It can be very time-consuming
b. High maintenance cost
c. Poor system performance due to complex data processing
  
JLS*** posted at 9/11/2017 10:39:19 AM
1. The most important criteria to be a successful framework include:
- Related records are connected
- Avoiding redundancy
- Quick and easy accessibility to finding data

2. The features most common in all logical data models include:
- Records
- Only singled value data
- Use of keys to identify records
- Records are organized, so it is easy to find the data

3. The advantages and disadvantages of a relational model include:
Advantages:
- Connects records using primary and foreign keys
- Independent of hardware and storage implementation
- Can handle large and complex data

Disadvantages:
- It can be costly to set up and maintain
- It could take a large amount of time to retrieve data because of large amounts of data
  
JCA*** posted at 9/9/2017 2:50:59 PM
1) what are the most important criteria to be a successful framework (or logical data model) to organize data?
It should connect all of the records logically and efficiently so that the data are easy to navigate and retrieve.

2) What features are common in all logical data models?
Records, which consist of an array of observations on one unique object, are linked (although by various ways depending on the model) and keys are utilized.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages include the fact that multiple records across the data set can be processed using a single operation, data are independent of hardware/software limitations. Disadvantages can arise from difficulty handling complex or especially duplicate data.   
AAZ*** posted at 9/6/2017 4:41:56 PM
1) The most important criteria to be a successful framework involves the following:
*Organization of records
*Avoiding redundancy when possible
*Accessibility
*Single-valued data
*Security
*Data-retrieval should be optimized in a timely matter.

2) The features that are common in all logical data models are:
*Has sets of data consisting of columns and rows
*Uses pointers, or relations for organization.
*Has only one data value.

3)The advantages and disadvantages of a relational model include:
Advantages:
*Better Security
*Efficient
*Hardware independant
*Easy to understand

Disadavantages
*Unable to handle Big Data
*Can't handle complex queries
*Can't handle data with multiple values.   
B_D*** posted at 9/6/2017 4:06:22 PM
1). The most important criteria for a successful framework are...
- No redundancy in the data
- Easy to navigate
- Related records should be connected
- Timely availability to retrieve the data

2). What features are common in all logical data models?
- Structured data that is well organized for easy navigation
- Use of keys for data identifiers
- Data is made of a single value

3). What are the advantages and disadvantages of a relational model?
Advantages:
- Not dependent on hardware
- Related records are easily connected and related
- High security and privacy of data

Disadvantages:
- Unable to process complex data
- Does not have ability to work with big data
- Performance is slowed or occurs issues if large amounts of data or is not single valued
  
JS3*** posted at 9/14/2016 2:38:42 PM
The most important criteria for a logical modal to be successful framework are:
1) Independent of software and hardware implementation
2) Non procedural and high level languages must be able to access the data
3)It should be naturally described.
Features common in Logical data models:
1) All are identified using keys
2) No redundancies
3) Data must be single valued
Advantages of Relational Model:
1) A relational model stacks the records in to tables which makes it easy to join the data across the tables with out complexity
2) It is single valued, no composite, and no redundancies
3) Independent of hardware and software implementation
4) Any modern high level languages can access the data in RDBMS.
Disadvantages:
1) Scaling up is complex and highly expensive
2) Cannot handle Big Data
3) Cannot store semi structured and unstructured data   
NAV*** posted at 9/12/2016 7:56:10 PM
1) Most important criteria to be a successful framework (or logical data model) to organize data
• Navigation through data should quick and easy
• Avoid redundancy by establish correct relationships between entities
• Should be able to process large amounts of data quickly
2) What features are common in all logical data models?
• Every logical data model has a basic unit of organization as a set of data on one object i.e. record or tuple
• Each piece of data should be single valued and not composite i.e. attributes
• Navigation through data is possible through different ways i.e. data is connected
• Every piece of data has identifier to connect to other pieces of data called key
3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
• Relational data model connects records by duplicating primary key values
• RDBMS is stacks records into relations describing data in natural way, which also reduces redundancy and increases processing speed.
• It is independent of hardware and storage implementation
Disadvantages:
• As the amount of data increases scaling techniques of big data are required.
• Getting unstructured data like videos, music into relations is difficult
• Building relations between semi structured like text messages is not possible
• As more and more big data is increasing following relational model is becoming complex.
  
NK8*** posted at 9/12/2016 7:29:11 PM
1) The most important criteria to be a successful framework (or logical data model) to organize data is to first plan the data to be simple and then accordingly organize the data. Related records should be well connected. Unnecessary redundancy should be avoided. All the attributes should be single-valued. Good connection between the records make the retrieval of data simple for huge amounts of transactions.
2) Data is represented in the form of collection of records. The records are collection of fields and all the fields are single valued. All of the data models are used to retrieve the data
3) Advantages:
It can handle complex data in an easier way through the well connection between the records.
It is not dependent on the hardware and the software implementation.
Data retrieval is easy for complex data. Security is high for the data.
Disadvantages:
It's costlier when compared with the other models.
If the data and queries are extremely complex, it may affect the processing time.
Sometimes duplication might happen.   
ADI*** posted at 9/12/2016 3:29:41 PM
1) The first and foremost important criteria while creating a data model is that it should be as simple as possible and structured.
Faster query: The data is we save is increasing exponentially day to day, so in order to make the queries faster it is required to retrieve less data. This can be achieved by filtering on the server end such as removing any obvious or unwanted columns.
Redundancy: In order to overcome this issue, Normalization of data should be done which in turn will help access data easily.
2) Entities, attributes and relations are common in all logical data models. Records are connected with one other in all the models.
3) Advantages:
Can handle complex queries.
It has the data stored in its natural form thus accessing and understanding is easy.
Better security than other models.
Disadvantages:
Relational model can handle complex queries which means it reduces the performance as the tables and relations become complicated.
Partial data retrieval is not possible which increases the time for data access.   
AD1*** posted at 9/12/2016 2:05:30 PM
1) what are the most important criteria to be a successful framework (or logical data model) to organize data?
• No redundancy in the data
• Fast retrieval for huge amounts of data
• Proper connections to ease accessibility

2) What features are common in all logical data models?
• Arranging data into records and Connecting records
3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages
• Easy to use and navigate because of its natural structure,
• Independent of hardware and storage implementation.
Disadvantages
• Expensive
• The execution may become slower than hierarchical database because of the complexity

  
KUN*** posted at 9/12/2016 1:25:47 PM
Most important criteria to be a successful framework (logical data model) to organize data
• Records should be well organized
• Related records should be connected
• Unnecessary redundancy should be avoided
• Objects should have multiple attributes
• Attributes should be single-valued
• Attributes should be relevant to the problem domain

What features are common in all logical data models?
• Data are represented by collections of records
• Each record is a collection of attributes (field, properties)
• Each attribute is single-valued
• Related records are connected

What are the advantages and disadvantages of the relational model as opposed to other logical models?
ADVANTAGES
• It can handle complex data
• It eliminates data duplicity
• Provides a means of describing data with its natural structure
• It is independent of hardware and storage implementation
• Provides basis for high-level, non-procedural language for accessing data
• The Programmer can specify single operations to be performed across the entire data set
• Data retrieval and manipulation is easier

DISADVANTAGES
• It is costlier to implement and manage
• Complex data and queries may impact performance
  
APA*** posted at 9/12/2016 12:47:28 PM
Q1. The most important criterion for a logical data model to be successful are following:
• Data should be complete, meaningful and well structured.
• We should be able to draw entities and clear relationships between them so as to avoid redundancy and quick retrieval.
• Data should be single valued no multi value and composite values are allowed.
• Data retrieval should be quick and efficient.

Q2. Common Features in all logical data model are:
• Data is converted to relations where every relation is a collection of records and fields.
• Every record is unique using primary key and every field of it has single value.
• Able to handle huge amount of data in such a way that its retrieval is easy.

Q3. Advantages & Disadvantages of relational model over other logical data models are:
Advantages:
• We are able to process several records at a time simultaneously leading to quick retrieval of data.
• Data are linked to each other by duplication of data instead of pointers making them independent of hardware and software.
• Multiple users can access the database at same point of time without getting any intervention from others.
Disadvantages:
• For a relational model to be efficient data should be well structured and well defined otherwise it can lead to failure.
• Its maintenance and set up cost is higher than any other model.
• If large amount of complex data with multiple relationships exist then data retrieval would not be efficient.
  
VKO*** posted at 9/12/2016 9:35:57 AM
1) what are the most important criteria to be a successful framework (or logical data model) to organize data?
For every logical data model to be successful, data should be complete and meaningful.
Should be able to draw decisions out of the framed data.
Should be able to access huge amount of data.
Data redundancy should be eliminated.

2) What features are common in all logical data models?
In all the models “Data” is represented as the collection of records. Every record is a collection of fields and they are single data valued.
All the models are used to draw decisions out of the data.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages
The Relational model was quickly adopted by the commercial users.
Multiple records can be processed using a single operation for the entire data set.
Data is independent of hardware and storage implementations.
Automatic navigation with a programming language.
Disadvantages
Relational model is costly compared to the other models.
Cannot handle extremely huge amounts of data.
  
RAV*** posted at 9/12/2016 1:14:54 AM

1Q) The basic important criteria’s are:
• Any logical data model that is being developed should not occupy more space(memory).
• They should be simple structured and easily accessible.
• Fetching of data should not take much time.
• Logical data models should have provisions to create indexes.

2Q)
• Any logical data model will be organized in a structure followed by connecting objects and their characteristics.
• All data models are easily expandable and can be updated
• Every unit of a column must contain single values and should be unique

3Q)
• Advantages
- Large amounts of data can be easily searched, maintained and different entities can be related using relations.
- Updating or removal of data can be done by deleting a Tuple(row,record).
- Data can be secured by creating a different entities that are authorized.

• Disadvantages.
- If the structure is really large it takes time to pull out the data.
- Complex data models requires more number of queries.
  
SNE*** posted at 9/12/2016 1:01:08 AM
1) What are the most important criteria to be a successful framework (or logical data model) to organize data?
• One of the important thing we have to keep in mind while building a data model is that we have to correlate different entities and establish correct relationship among them . This makes it easier for the user to retrieve the required data.
• Redundancy must be avoided.
• If large amount of data must be organized it should be done in an appropriate way , so that the user will not have difficult to access the data.

2) What features are common in all logical data models?
• All logical data models consist of entities , attributes and relationships.
• The main aim of all of them is to organize data , so that it is easy to retrieve.
• Data is single valued.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
In relational data model , data is organized in the form of tables consisting of rows and columns. The tables are linked to each other by special entities known as keys.
ADVANTAGES:
• The accessing of data is easy as the data is organized in a systematic manner.
• The records have unique keys which makes it easier to locate the data.
• The relationship between the entities gives us an overall view of the task at hand.
DISADVANTAGES
• If there are a large number of tables between whom the relationships have to be made , it results in complexity of data.
• Complexity of data in turn effects its performance.


  
SY4*** posted at 9/12/2016 12:41:10 AM
1. The most important criteria for framework to be successful is make sure all the data is well organized and well structured. Secondly, Accurate data should be easily accessible. We have to make sure the redundancy of data should be eliminated and also consistent data should be maintained. Lastly, this framework should meet all the business requirements.

2. Coming to features which are common in all logical data model, I understood that data here is formed by grouping similar entities together. These entities have something called single valued attributes which represents their features. Secondly, the data should be well structured. Lastly, they allow normalization.

3. Advantages of Relational Model:
* Duplication of data can be overcome.
* Data can be understood with ease because it is well structured.
* Security of data is high.
* Data retrieval is simpler compare to other data models.
* Redundancy is avoided over here. So it increases the efficiency of the system.

Disadvantages of Relational Model:
* The cost is high for setting up and maintaining RDBMS
* Large amounts of data can make the system complex and slow. It becomes hard to retrieve data at that moment.
* Unstructured data can lead the present model design fail.
  
ARU*** posted at 9/11/2016 11:44:15 PM
1) What are the most important criteria to be a successful framework (or logical data model) to organize data?
Each field of a record must be single-valued. Duplication of data should be avoided. Data must satisfy the constraints of the model developed. All the data must be easily accessible through logical relationships and the time taken to do so should be minimal.

2) What features are common in all logical data models?
All the data models consist of entities, attributes and relationships. Data is normalized in all the logical data models. Primary key is specified.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages: Relational model enabled processing several records simultaneously instead of processing one record at a time. Data independence from hardware and software was possible. Relational model is easy to design.
Disadvantages: As the complexity increases, relational model may not be efficient.
  
PB5*** posted at 9/11/2016 11:21:30 PM
1. The most important criteria for a successful frame work in organizing data are:
• The data must be relevant to the considered business case and it must be free from redundancy.
• One record must be connected to the other with valid logic which makes it easy during data retrieval and to navigate between data.
• Moreover, the relation or connection between the data must be made reliable, so that it can accommodate the addition of new data to the existing data with minimal modifications to the structure.
• The model must be independent of the hardware and software components, so that the intricacies in the data can be explored more effectively.
2. The common features in all the logical data models are:
• The data is represented by the collection of records.
• Each record is single valued and are connected to each other by pointers, relations or objects.
3. Advantages & Disadvantages of Relational model:
Advantages:
• The relational model is capable of handling more complex data compared to other logical models.
• Navigation through the data is made easy by relating the data.
• All the objects in an entity set are connected naturally and thereby no need of separate relation for internal data.
• Due to relations and constraints for each data set, high security is assured.
• Multiple users can access the database at same point of time with-out any intervention.
Disadvantages:
• Cost for the implementation of relational model is high due to the complexity involved in building the relations to the data.
• The time for retrieval of the data is high in the case we are dealing with huge amounts of data.
  
ABH*** posted at 9/11/2016 11:18:55 PM
1.To be the successful framework to organize the data, that framework should be able to navigate across the data by connecting the records, data processing time should be faster and the framework should be built in such a way that that the data quality, availability and security should never be at stake.

2.since the data organization in all the logical data models is done by creating “records” which is the basic storage unit of organization.Therefore the common features in all the logical data models are:
a.Each record must be identifiable
b.Each piece of data should be single valued.

3.Advantages:
a.Single operation can perform a search across entire dataset
b.Relational model can access multiple types of information
c.It can link multiple records by sharing the common column
d.Processing time is faster since the data is organized in the form of tables
Disadvantages:
a.Difficulty in handling complex data
b.If there are more number of table, connecting the records becomes difficult.

  
MMO*** posted at 9/11/2016 11:18:22 PM
1. The most important criteria to organize data are as follows:
- Data is organized in a logical manner so that it can easily be maintained and communicated to the business
- Quickly accessible to all necessary parties within the company
- Standardized and controlled so that there is a high level of data integrity and reporting is more efficient
- Secure to protect data privacy rights in various regions
- Ability to link primary keys amongst various tables
2. Features that are common in all logical data models are that all records have various attributes that describe a single entity. These records are able to be linked inn all logical data models. The difference is how the associates are made within each data model.
3. Advantages and disadvantages of the relational model are as follows:
- Advantages:
o Data is linked allowing for more efficient queries
o Data is described in its natural structure
o Reports can be created off of the full database, rather than just a table at a time
o Reports can be more dynamic due to the availability of data, issues/opportunities may be identified through this visibility
- Disadvantages:
o As database grows, cost of housing the data may increase depending on storage capabilities
o Larger databases can sometimes has irrelevant data that cannot be efficiently managed leading to wasted storage space
o If multiple people are managing database, there may be duplicate data (columns, tables, IDs) if there are not standard processes on maintaining the database   
SP2*** posted at 9/11/2016 11:13:10 PM
Q1) The following are some important criteria to be a successful Logical data model:
To identify objects relevant to the business question. To identify attributes which are relevant and they should be single valued. The relationships between the objects should be defined accurately. The data should be well organized and the database should be easily accessible.
Q2) In all Logical data models, data is represented by collection of records. Each record is collection of attributes wherein each attribute is single valued. The records are connected in all Logical data models.
Q3) Advantages: Data is well organized and redundancy is reduced. With the help of relational model, we can describe data with its natural structure, independent of hardware and storage implementation. We can specify single operation that can be performed across the entire dataset.
Disadvantages: Processing time will be slow when dealing with large and complex datasets.
  
NAN*** posted at 9/11/2016 8:59:31 PM
1) what are the most important criteria to be a successful framework (or logical data model) to organize data?

* The data should not be redundant.
* The data has to be highly secured.
* Data integrity has to be maintained.
* Multiple users should be able to access the data simultaneously.
* It has to be independent of the hardware and the software

2) What features are common in all logical data models?

All the data models are represented as a collection of records and each record has to be unique.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages
1. Supports data independence
2. Relational model is simple and flexible
3. It is highly secure as authorization can be implemented easily.
4. Reduces redundancy of information.
5. Data is independent
Disadvantages
1.Searching for a data or information can take extra time as compared to other methods



  
SJ1*** posted at 9/11/2016 8:18:53 PM
1) What are most important criteria to be a successful framework (or logical data model) to organize the data?
1) Database should be designed in such a way that it meets the business requirements correctly using the minimum hardware and cost. Addition of infrastructure for future requirements should be with the minimal or no change to the existing hardware or design.
2) Each record must be uniquely identified, relevant to the business case, each piece of data should be single valued and no redundancy in the data.
3) Data retrieval with minimum query execution time.
4)Proper backup plan, replication plans for any disaster recovery.

2) What features are common in all logical data models?
Common Features among all logical data are:
1) Each record must be uniquely identified
2) Each piece of data should be single valued.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
1) Similar records are stacked together, which helps in easy retrieval of the data when queried and also removes data inconsistencies.
2) Most of the cases there is no Data redundancy or is limited.
3) Addition/Modification of attributes/fields to the existing table structure is easier.
Disadvantages:
1) Cost of the hardware used (for building, maintaining and to back-up the data) in relational model is comparatively high.
2) Cannot handle huge amount of data.






  
VIV*** posted at 9/11/2016 3:59:30 PM
1)Understanding, analyzing and correct representation are the most important criteria to be a successful framework.In addition to that fast data retrieval, easy accessibility count too.

2)Every logical data models has sets of data consisting of columns, rows related by various pointers,relations which contain one and only one data value.

3)Instead of processing one record at a time, a programmer can use the language to specify operations that would be performed across the entire data set.

Time required to set the data model is higher than others. It requires a process to be followed to create duplicate keys and organize them.   
SHE*** posted at 9/10/2016 3:43:54 PM
1) What are the most important criteria to be a successful framework (or logical data model) to organize data?
For a framework or logical data model to be successful it has to match or at least outperform other competitors in market demand and needs of organizations to managing different type’s data. A data model which is versatile in nature has better chances to survive in the market. And at the same time efficiency of the operations handled will have to be kept high. Having a well-organized data backed with technology making accessing of data easy.
2) What features are common in all logical data models?
All the logical data models are built to process and access the data in more efficient and meaningful way. They all are dependent on the accuracy of data entry for productive functioning.
3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
• Relational model links the data records by sharing common columns enabling a better functioning.
• Changing or modifying data became easy
• Controlling data redundancy
Disadvantages:
• Difficulty in handling complex data
  
FF2*** posted at 9/10/2016 10:34:15 AM
1. What are the most important criteria to be a successful framework (or logical data model) to organize data?

Most important criteria for a framework (or logical model) to be successful is its data. Data should be accurate, complete, relevant and reliable to organize.
Data entered in each field/attribute must be single valued.

2. What features are common in all logical data models?

The common feature in all the logical data models is collecting, storing, manipulating and retrieving of data if required. Records are connected to each other, either it may be through pointers or functional keys. Data stored in each attribute is single valued.

3. What are the advantages and disadvantages of the relational model as opposed to other logical models?

When compared to other logical data models, relational database model has many advantages. Data is organised in the form of tables and connected to each other through relations. Data model is easier to understand and flexible to use. The user can easily create, manipulate and pull any information in rows and columns and join different data and pull out a form of required format.

One major constraint and disadvantage in using of relational database is machine performance. Increase in amount of data, number of tables and relationships effect performance and response to SQL queries.   
FF2*** posted at 9/10/2016 10:34:15 AM
1. What are the most important criteria to be a successful framework (or logical data model) to organize data?

Most important criteria for a framework (or logical model) to be successful is its data. Data should be accurate, complete, relevant and reliable to organize.
Data entered in each field/attribute must be single valued.

2. What features are common in all logical data models?

The common feature in all the logical data models is collecting, storing, manipulating and retrieving of data if required. Records are connected to each other, either it may be through pointers or functional keys. Data stored in each attribute is single valued.

3. What are the advantages and disadvantages of the relational model as opposed to other logical models?

When compared to other logical data models, relational database model has many advantages. Data is organised in the form of tables and connected to each other through relations. Data model is easier to understand and flexible to use. The user can easily create, manipulate and pull any information in rows and columns and join different data and pull out a form of required format.

One major constraint and disadvantage in using of relational database is machine performance. Increase in amount of data, number of tables and relationships effect performance and response to SQL queries.   
PGO*** posted at 9/9/2016 6:44:40 PM
1)What are the most important criteria to be a successful framework (or logical data model) to organize data?
The most important criteria is
• Data should be normalized and well organised .This insures that we can easily navigate between data.
• There should not be any data redundancy.
• Data must be able to retrieved faster.

2) What features are common in all logical data models?
The common features of all logical models are
• Includes all entities and relationships among them.
• All attributes for each entity are specified.
• The primary key for each entity is specified. Each record is uniquely identifiable.
• Each piece of data must be single valued.
• Foreign keys (keys identifying the relationship between different entities) are specified.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
1. The revision of any information as tables consisting of rows and columns is much easier to understand .Data is represented as collection of well organised records.

2. Different tables from which information has to be linked and extracted can be easily manipulated by operators such as joins and queries to give information in the form in which it is desired.

3. The usage of relational algebra and relational calculus in the manipulation of he relations between the tables ensures that there is no ambiguity, which may otherwise arise in establishing the linkages in a complicated network type database.

Disadvantages :

1. A major constraint and therefore disadvantage in the use of relational database system is machine performance. If the number of tables between which relationships to be established are large and the tables themselves effect the performance in responding to the sql queries.
2.The cost for setting up and maintaining relational database can be expensive.
  
SWA*** posted at 9/8/2016 8:09:27 PM
1) What are the most important criteria to be a successful framework (or logical data model) to organize data?
1. The database should be able to store large amounts of data.
2. Data should be linked.
3. Data should be easily and quickly retrievable.
4. Ability to process data real time.
5. Should be cost effective.
6. Should be independent of hardware and software.

2) What features are common in all logical data models?

In all the logical models, data are represented by collections of records. Each record is a collection of fields (attributes, properties), each of which contains one and only one data value.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?

Advantages of relational model:
1. Data independence from hardware and storage implementation.
2. Non procedural language for accessing data.
3. Ability to perform single operation over the entire dataset.
4. Limits duplication of data.
5. Data inconsistencies can be avoided by storing and maintaining the data in one place.

Disadvantages:
1. Joining too many tables sometimes can result in cumbersome & inefficient queries.
2. Representing complex data types can be difficult.
  
NM9*** posted at 9/8/2016 2:50:51 AM
1) what are the most important criteria to be a successful framework (or logical data model) to organize data?
1) Easy to use data fetching such as a nonprocedural language SQL used for accessing data.
2) Powerful: Fetch large amounts of data quickly, easy to operate such as describing data with its natural structure only.
3) Independent of Hardware and Operating system.

2) What features are common in all logical data models?
Records/entities, need for relating the records to fetch data, uniqueness of each record.

3) 3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
a) Speed: Relational models are much faster compared to the pointer based network and hierarchial models.
b) Ability to store large amounts of data.
c) Easy to load and fetch data
d) Ability to perform complex calculations(joins..) with much ease as compared to counterparts
Disadvantages
a) Prone to duplication and errors while updating.
b) Fetching unnecessary data such as fetching a whole record when we need a part of it.
c) Complex calculations consume more time
  
JEC*** posted at 9/7/2016 5:01:17 PM
1)When creating models you need to make sure that the data is well organized and that the data is not being repeated. The data needs to obviously state what object it was observed from.
2)Features that are common in data models are objects, attributes and relationships. These objects should contain single value items. This way the data can be easily sorted through and found.
3)The advantages are that there are less errors present and the relations are stacked upon each other. It is also easier to navigate through. The disadvantages are that it has a higher cost of managing and creating. It also has a disadvantage of needing a higher computer output and capability.   
NJW*** posted at 9/7/2016 4:21:55 PM
1) models like this need to be able to take large amounts of data and efficiently organize them in to categories that a reader can quickly understand and interpret.

2)All Data models will contain records, and these records will be connected to other records in the model in order to create relationships. They will also be completely unique from any other records in the model. The data should also be well organized.

3) Relational models are good because they are very efficient and easy to navigate and they are independent from hardware or storage constrictions. They are bad because they lack the ability to sort and categorize complex data and are prone to mistakes because of re-entered data.   
JAK*** posted at 9/7/2016 12:46:18 PM
1)These models need to efficiently organize data in a way which creates little to no overlap between observations. They need to have relevancy in how they are organized and what they are comprised of. It needs to provide a method of accessing data quickly and with accuracy.
2) Commonalities include records, which contain data in single valued forms. The records are also uniquely identifiable and are connected to other records, which vary depending on which database model is used.
3)It is relatively simplistic and independent from hardware and storage, but also can have difficulty handling complex data.   
KTW*** posted at 9/6/2016 6:09:14 PM
1) The model needs a way to distill large amounts of data and organize the relevant pieces to the object that it was observed upon. It has to then be able to connect the relevant records together – both by creating and breaking those connections. All of this is brought together by being able to navigate the data and select record based on input criteria.

2) All models; have ways to navigate data, records have a way of being identified, and records are connected to other records.

3) The advantages are that the relational model is independent of hardware and storage, multiple records can be navigated, and it provides an approachable setting for storing/accessing data. The disadvantages are that it has difficulty in handling complex data and it requires thoughtful setup to eliminate duplicate data.
  
RZW*** posted at 9/6/2016 4:08:16 PM
1) The most important criteria for a logical data model to be successful is for it to be able to successfully organize data in a manner that is easy for users to read and navigate through.

2) Common features in all logical data models include good organization, connections made between data, no redundancy, and all records are uniquely identifiable.

3) Advantages: efficient, easy to navigate and retrieve data, and use of primary and foreign keys. Disadvantages: costly, uses up a lot of storage, and can be slow.   
QBS*** posted at 9/5/2016 11:17:27 PM
1. I think the most important logical data models should be an organized system that allows for easy navigation and to be user friendly, have high speed and accuracy as well as meet the users needs and wants, as well as relevant data for the user.

2. The features common in all logical models are the connections between data and records, the data is well organized, records are single valued and there is no redundancy.

3. The advantages of relational data models is the efficiency of the model, data is stored and stacked into tables with similar data, data retrieval is easier. The disadvantages of relational data models are the storage capabilities, slower extraction of data and broken keys or records.   
MK1*** posted at 9/5/2016 8:19:59 PM
1) The most important criteria a logical data model should have in order to be considered a successful framework include: the ability to hold lots of data, a well-organized system that allows the database to be organized efficiently and has logic that makes sense and is easy to follow. It must also be secure and quick.

2) All logical data models include specific features; these include: independence from any specific database management product or hardware, all records are uniquely identifiable, all data is represented through records and has specified attributes, as well as unique primary and foreign keys.

3)Advantages of using a relational model include: makes querying and processing records efficient, freedom or independence of usage from hardware or software, operations or commands can be processed and applied to whole data set as opposed to one by one. Because the relational database is set up in stacks or tables, data or records can share attributes, it is easy to understand, and has automatic navigation. Another advantage is the high level SQL language, which is easy for the programmer to use.
Some disadvantages include: high cost of maintenance, handling complexly related data can become difficult through a relational database. There is also a disadvantage in the limitation of data: all fields must hold only single- values; the relational DB records do not have the ability to hold multivalued data. Another disadvantage is speed- If the tables between the relations are large and hold many attributes or data, machine performance or retrieval can be slow.
  
PGI*** posted at 9/5/2016 1:34:20 PM
he most important criteria to be a successful framework is that its independent of hardware and storage implementation. security is another important feature. And also speed of retrieval.

What is common to all the logical data models is that data are represented as collection of records of one entity or one object.

The advantage of relational database is the use of primary key or indexing. It provides a means of describing data with its natural structure and provides a high-level, non-procedural language for accessing data. Instead of processing one at a time the whole data set can be accessed using a query language.   
EPE*** posted at 9/5/2016 12:51:38 PM
1) I think in order to be considered a successful framework, the data must be stored and organized in an orderly fashion. This will help to limit the time it will take for end users to access the data that they need.

2) All logical models share the idea that all records are uniquely identifiable. They also share the fact that every piece of data must have a unique value. They also share an idea that records are connected. All of this is accomplished differently throughout the various models, but it is present in some way or another.

3) Advantages: Better performance due to its efficiency and independent of hardware and
software
Disadvantage: Can be costly to run and maintain
  
ZHA*** posted at 9/5/2016 12:18:06 AM
1. First, a successful framework should be user-oriented to meet users' demanding needs. Second, it is able to process large amounts of data. Third, data collection methods should be as accurate, accessible and affordable as possible.
2. I think all logical data models have the features as follow:
a). The models' data are collected as records. Every record should be uniquely identified and each of data is of a single value.
b). The models' data collections and data-mining methods are based on 3 Vs， which are volume, variety and velocity.
c). A record can be used in multifaceted ways.
3. Advantages: a). The relational model can share common attributes.
b). The data can be independent from hardware and storage implementation.
c). Its navigation is automatic.
d). Its operations can be specifically conducted in a whole data set.
e). It includes high integrity and soundness.
Disadvantages: a). The model is hard to process complex data.
b). It creates high maintenance fees.
c). It requires high-level computation with a large quantity of data.
d). Increasing demand for renewal of products relevant to the model.   
XW3*** posted at 9/1/2016 1:23:09 PM
My understanding of the three questions are here:
Of question 1: A successful data management framework should provide means to describe data and provide means for users to access the entire data specifically and accurately.
Of question 2: in all data models, data are presented as collections of records. Each records has only one data value. For logical data models, hierarchical and network, all the collection of records are collected by pointers.
Of question 3: the advantages of relational model are that data in the system are independent from hardware and storage and that it is easy to navigate the whole data set. The disadvantage of the relational model is that the model has limitations on handling complex data.   
RR1*** posted at 9/20/2015 12:50:16 PM
1) what are the most important criteria to be a successful framework (or logical data model) to organize data?
A) For any framework to be successful it should be independent of underlying software and hardware. The framework should connect all tuples and should take minimum time to navigate through logically. The date should be less complicated and should be able to retrieve it easily.

2) What features are common in all logical data models?
A) It includes all the relationship between the entities . All these have the single values and they are logically connected.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
A)
Advantages:
1) There are less errors present due to the lower redundancy values.
2) Accessing data is easier due to the efficient due to simplicity.
3) It is independent of the hardware & software structure.

Disadvantages:
1) The performance of the system is affected due to the complexity of the tables and data.
2) Implementation cost jumps up due to the hardware complexity which even increase time for the retrieval.
  
SS4*** posted at 9/16/2015 2:45:18 PM
1) what are the most important criteria to be a successful framework (or logical data model) to organize data?
The main purpose of a framework is to well organize data which come from many sources.
A successful framework should be able to logically connect all tuples and should take minimum time to navigate among the data sets. It should also reduce redundancy of data.

2) What features are common in all logical data models?
All logical models have the data as the collection of records where each record is a collection of fields. Each field is a tuple having single value. The data in these models are logically connected and enables us to navigate through the records.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
The advantages of relational model are:
1. Data is stored in natural format
2. Data is independent of hardware or software implementation
3. It is basis for non procedural languages to access data
4. We can access data set at once instead of single operation for each transaction
5. There are no pointers between records

The disadvantages are:
1. Complexity increases while handling large volumes of data like Big Data in terms of normalizing data and building relationships.
2. Only efficient building of relationships can reduce data redundancy   
KIR*** posted at 9/14/2015 8:09:10 PM
1) what are the most important criteria to be a successful framework (or logical data model) to organize data?
Few of the most important criteria are, that the framework should be connected between one another for easy navigability while serving the foundation for a physical data model. Also, a successful framework should be feasible to be compatible with any of the business objectives.

2) What features are common in all logical data models?
Data is represented by collection of records/entities.
And each entity/record is a collection various attributes
And each attribute should be having only one value


3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
-Because there is no redundancy, there is very less chances of errors and that makes it very efficient.
-When we have an efficient system, accessing data is going to be very fast. Also managing the data is easy.
-Because the information is divided into entities, applying security levels and making it accessible according to the permissions are easy.
-We can normalize the system very well.

Disadvantages:
-As the system gets more and more entities/tables, it becomes very complicated. It has very high adverse effect on the performance.
-Relational data model is not that capable of handling huge amount of information/data which can also be in different forms and irrelevant. Like Big Data   
PHI*** posted at 9/14/2015 7:48:33 PM
1. Data modelling depends mainly on the relationship between the data objects. The framework to organize data is said to be successful when the requirements for the application are met. We need to consider how the data is processed this could be done by usage of data by application in queries or any updates or the structure where the data is inheriting itself.

2.a. Include entities and their relationships
b. The primary key is specified
c. They also consist of foreign keys
d. Describe data requirements
e. Entities and attributes are defined.

Advantages
a. There is no effect on data access If there are any changes to the database structure.
b. Relational model is much simpler than other data models.
c. Data can be encrypted and stored.
d. Complex querying is possible with performance improved access, write and delete.

Disadvantages
a. The ease of design could lead to a poor database structure.
b. May cause data duplication, data redundancy and data inconsistency.
c. Setting up and maintaining the relational data model is expensive as it requires special and more powerful software.   
SAN*** posted at 9/14/2015 7:43:56 PM
1. A logical data model is the one which represents the organizations business process. For the organization to be successful, it should not have any duplication of the data and should be accessible across the organization. For the organization to be successful, it should have its data well organized.

2. Few common features have already been discussed in the earlier responses. Defines entities and relationships between them. They store and retrieve data. Organizing all the unstructured data which in turn helps business process streamline.

3. Advantages: The data model design, maintenance and implementation is much easier making it both data and structure independent. Better security for certain tables where we can make them user-specific
Disadvantages: Relational databases are widely used in many industries but they have expensive settings and maintenance. But now-a-days data is more valuable than the setting up of the company. Duplication of data is possible which results in redundancies.   
KRI*** posted at 9/14/2015 7:40:10 PM
For a framework to be successful, the retrieval of records should be possible with as less time as possible since real time queries can fetch millions of records at a time. A common feature among all data models that comprise of the logical model is that data is always stored as records, and this information stored in records is interconnected. The only difference is the way it is organized and the mechanisms used to fetch this data. A major advantage of relational model is that data is store effectively. Making a change to a specific record will reflect changes to all other tables having a link to that data. Complex DML queries that are complex can be carried out without much effort, in other words, no high-level language is needed to access data. One of the disadvantage is that for relational databases need high hardware capabilities to run efficiently, especially if the data sources are in remote locations.   
SS3*** posted at 9/14/2015 7:38:32 PM
The most important criteria for a successful framework is ease of access and use. The data should be organized in such a way that it can be sorted, extracted and manipulated according to the user requirement by using simple code. The most common features in all the logical data models is the storage of data is in form of records and all the records are lined in one way or the other. Also, no field is allowed to have multiple values in any of the models. Major advantage of relational data model is data independence from h/w and storage implementation. Also, the automatic navigation features adds to the capabilities. Disadvantage of Relational Database is the complexity faced in managing data into multiple complex relationships.   
PRI*** posted at 9/14/2015 6:52:18 PM
CRITEREA FOR SUCCESSFUL LOGICAL DATA MODEL
1. Independent of underlying software and hardware.
2. Capable to handle complex entities and relationship.
3. Data Redundancy should be minimum.
4. Easy to understand and interpret.
5. Minimum hardware space should be occupied.
6. Model should be Robust.

COMMON FEATURES OF LOGICAL DATA MODEL
1. All entities have Primary Key.
2. Required attributes are mentioned for all entities
3. Relationship between entities are mentioned.
4. Cardinality and Optionality may or may not be represented.
ADVANTAGES OF RDMS OVER LOGICAL DATA MODEL
1. It is simple to modify details with more efficiency.
2. These can give a good security to data by providing different levels of permissions to its users.
3. It is built in such a way that further building blocks can be built easily.
4. It is data independent from hardware and storage
5. Automatic navigation, non-procedural language for accessing data.
DISADVANTAGES OF RDMS OVER LOGICAL DATA MODEL
1. With higher ability to handle complex data, a person with higher database skills is necessary to operate this.
2. A database with very complex data structures may require more powerful servers to return results within an acceptable response time.
  
SK1*** posted at 9/14/2015 6:38:17 PM
1)
To organize the data successfully, the following criteria should be taken into consideration for a data model
-The data model should be able to organize the data as per the requirement
-Security of the data is most important and unauthorized access to data must be prohibited.
-It should avoid the redundancy in the data
-It should be able to logically connect to different tables without mismatch
-It should be able to retrieve the data quickly and efficiently, that is as time and accuracy is important.
-It should be easily understood and maintained.
-It should allow multiple technologies for data access and should be platform independent.

2)
The common feature in all the logical data models is that they have organized data with some connection among the different records. And these models store the data which is retrievable, deleted and updated.

3) The advantages and disadvantages of relational model are as follows.

Advantages:
- Data implementation from hardware and storage implementation is achieved through relation model
- Data can be accessed by automatic navigation, or a high-level, non procedural language which would be easy to access the data across entire data set.
- Data can be easily manipulated and extracted with different operators.
- Security of the data and authorization can be controlled easily.
- Normalization

Disadvantages:
- It is not easy to transform into relational database model from other logical models.
- If the number of tables which are related to many other tables are more, then it would be difficult for the sql queries to respond.

  
NAR*** posted at 9/14/2015 6:38:12 PM
). Records of data should be structured with having relation between the tables. Each table having a defined primary or unique key and a foreign key will help to eliminate the duplicate data. Having cardinality provides information on how the entities in the tables are related and data can be easily accessible.
2). Primary key and foreign keys for each of the specified entity is defined. It includes entities and relation among them.
3). Advantage:
Usage of DML is easy in the way the query is send to get the data in the relational database. Flexibility in linking and extracting the data using various operators and the way the table is structured into rows and columns is easy to use.
Disadvantages: Extracting data is slow in some of the cases, example hierarchical model. Operation depends on the consumption of the physical memory of the system.
  
SAR*** posted at 9/14/2015 6:31:55 PM
Important Criteria:

Successful logical data model should support the information stored to conceputalized, structured and manipulated independently.

Supports securing the data privacy.

Easy access of data should be made available

Common Features:
The way the data has been organized remains same in all logical database models.. Data is grouped into collection of records. Each record consists of attributes that consists of a single value


Advantages:

1 Each records can be related to other records in relational database.

2 Relational database links records by sharing common columns which allows connecting multiple connections between different tables

3 With the help of relational model, computations/operations can be performed for the entire data set

4 Provides rapid access to the data

Disadvantages:
1 Skills required to develop complex data accessing queries
2 Designing the database becomes complex when many tables/entities are involved   
PRA*** posted at 9/14/2015 6:24:43 PM
1) what are the most important criteria to be a successful framework (or logical data model) to organize data?
-Data should be well organized with less repetition.
-Data should be manipulated easily.
-Data should be retrieved with less effort.

2) What features are common in all logical data models?
All logical data models enables the users to store the data, retrieve the data and manipulate the data in an efficient manner.It should be user friendly.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
-Increases the integrity of the data by reducing the redundancy.
-Data can be organized in a more efficient way.
-Data can be easily manipulated.
Disadvantages:
-Unstructured data can't be processed.
-Costly to implement this data model.
  
SUM*** posted at 9/14/2015 4:55:02 PM
1) What are the most important criteria to be a successful framework (or logical data model) to organize data?

• A data model should establish relationship between the entities for easy navigability.
• It should serve the basis for physical data model.
• It should serve the purpose of having a better communication between business objectives.
• A successful data model should have records connected to one another and also be relatable.

2) What features are common in all logical data models?

• Logical data models involve normalization.
• It includes entities and attributes which specify the data.
• Relationship exists between the entities and it helps in specifying the cardinality between them.
• Logical data model includes primary and foreign keys.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?

Advantages
• Using relational database complex queries like DML statements can be carried out.
• Data is stored once but it can be manipulated any number of times as per the business requirements.
• It provides better data security.
• With the usage of relational databases, the ambiguity related to data can be avoided.
Disadvantages
• The main disadvantage in using relational database is, it affects performance of machine if the numbers of tables are large for establishing a relationship between them.
• Limitations on field lengths can lead to data loss.
• The cost for setting up and maintaining relational database can be expensive.
  
SRE*** posted at 9/14/2015 4:36:28 PM
1)The most important criteria to be a successful framework to organize data are
- Data should be represented by collection of well-organized records;
- Records are all connected to navigate to related records.
- Avoid redundancies and should easily accessible
- Should meet all the business requirements.
2)The common features in all the logical model are ,Each attribute must have single value and each attribute must be relevant and Organized and structured data.
3)The advantages are
-The relational model links records by sharing common columns.
-Security is high.
-It provides basis for high level language for accessing data.
The disadvantages are
-Implementation is of high cost and high maintainance.
  
RK8*** posted at 9/14/2015 4:35:59 PM
Q1.
The important criteria for a successful framework are as mentioned below:
The data normalization is very important
The frame work should be designed to reduce the data redundancy
The data should be organized in a way to increase the efficiency of its retrieval

Q2.
The common features in all the Logical data models are as mentioned below
Data normalization
Attributes having a single value
Data is organized so as to have an easy retrieval of it
Relationships between them

Q3.
Advantages:
Ease of accessibility and usage
Decreased redundancy
The data durability and the security is high

Disadvantages:
The cost incurred to maintain is high
More data complexity leads to complex queries and time to retrieve data   
ARU*** posted at 9/14/2015 3:21:18 PM
1)what are the most important criteria to be a successful framework (or logical data model) to organize data?
Logical data model is a data model which represents the detailed organization’s data and the business concepts. Following are the important criteria for a successful logical data model framework
• Data structure is well organized and structured.
• Data should be easily accessible
• Data should be well structured to avoid the redundancy and duplication.
• The most important criteria for successful framework is it should be more efficient and easy to maintain.
• Should avoid complex structures.

2) What features are common in all logical data models (LDM) ?
• All the Logical data models should include all the necessary entities, attributes, key groups and relationships that represents the business requirements and business rules.
• Data are well organized and structured for easier navigation.
• Data in all the LDM are grouped by similar entities that are connected and have relation between them.
• Every attribute will have only one data
• Every entities and attributes uses business names.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?

Advantage:
• No data redundancy , data storage can be optimized
• Data Retrieval is simpler than other logical models.
• Relational Model is more effective than other logical models.
• Data modification can be done
Disadvantage:
• When data is huge, retrieval of data takes more time
• Expert to handle complex structures
• Implementation cost is high
  
JAC*** posted at 9/14/2015 3:08:32 PM
1)What are the most important criteria to be a successful framework (or logical data model) to organize data?
A Database is a set of data organized by a logical data model. In this model, data is represented by collection of records and each record is collection of attributes, which contains unique value. The following are the important criteria to be a successful framework:
-Related Data to be connected
-Redundancy to be minimized/avoided
-Easy accessible and user friendly UI

2) What features are common in all logical data models?
The following are the features that are common in all logical data models:
-Objects, attributes, relationships
-Collection of records
-Storing and retrieving data

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
-Storage and implementation independent
-Data redundancy is controlled
-Data is easily accessible
-Modification of data is simple
Disadvantages:
-Works good for structured data
-Handling of complex data is difficult and effects performance
-High maintenance cost
  
ABH*** posted at 9/14/2015 2:55:04 PM
1) What are the most important criteria to be a successful framework (or logical data model) to organize data?

As far as my opinion goes, the most important criteria is that the data should be structured and easily accessible to the user. Having said that , I also think that the user should understand the relationship between the data records and this can happen only when the data is stored in a logical manner. I would want to add one more point that I feel is critical or an important criteria in order to be a successful framework is that data redundancy should be as less as possible.

2) What features are common in all logical data models?

I would say one of the common feature or the goal at hand is to make sure that the data is as structured and organized as possible so that it is easy to retrieve when required. In a logical data model, all entities have attributes and primary keys defined for them. Also, for all logical data models identifying entities and relationships between them is very important.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?

The advantages of the relational model are as follows:

1)The actions can be performed on the whole data set rather than just a small part of the data.
2) The data is in an organized form where data is sub-divided into tables, rows and columns that makes it more clear and understandable to the user.
3) Data Redundancy can be reduced resulting in more consistent data and hence an improved or efficient database.

The Dis-advantages of the relational model are as follows:

1) As I have mentioned in the advantages that large amounts of data are processed. But sometimes due to this complexity increases and it can be pretty time consuming.

2) The maintenance cost is also high since it involves handling large amounts of data.

3) Sometimes when complex queries are involved it may affect the performance of the entire system.
  
RAH*** posted at 9/14/2015 2:28:26 PM
1) What are the most important criteria to be a successful framework (or logical data model) to organize data?

• The logical data model needs to include all the entities, attributes and relationships which represent the business and it must define the business rules very clearly.
• A successful logical data model should streamline the physical design process with clearly substantiating the data structures and the relationships between them.
• Also a good logical data model needs to be created keeping in mind the current as well as the future business requirements.
• The records in the data model need to be well organized so that navigation is easy.

2) What features are common in all logical data models?

• All logical data models are designed and developed to be independent of DBMS, technology, etc.
• It basically describes the data requirements of a project.
• The entities and attributes will have definitions.
• The relationships between the entities say about the cardinality and optionality of the relationship.
• The primary and the foreign keys are specified.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?

Advantages
• The relational model is flexible as the data from the tables can be extracted and manipulated easily in the format that is needed.
• With the aid of normalization we can achieve data independence easily.
• Using relational model helps in catering to future requirements.
• Data security can be achieved by having authorization controls.
Disadvantages
• One of the key disadvantages of the relational model is its machine performance to responding to the queries.
• Since the relational model doesn’t force to impose coherent table, programmers might create unnecessary complexity by choosing the wrong data types.
• Complex queries require highly sophisticated hardware to return the results in a stipulated response time.

  
MP1*** posted at 9/14/2015 2:15:48 PM
1ans : Below are the most important criteria’s of a successful logical data model
1.Data Accessibility: There is a large amount of data in every large organization. These data must be collected, stored and should be easily retrieved.
2.Data should be well organized, i.e records are connected in such a way that records can be navigated to related one’s
3.Data redundancy should be avoided.

2Ans: All logical data models includes tables, attributes and relationships. They have tuples and each tuple have an identifier.

3Ans : Advantages of relational model
1. Normalization structure is used in relational model whereas loops are used in network model. Relational model doesn’t have pointers which enables users to retrieve the data easily.
2. Sql query is used in relational data. It is user friendly and the data can be queried and manipulated using DML statements like select, update and delete.
3. Data is stored in rows and columns which is much easier to understand.
Disadvantages:
1. Querying data consumes more time when trying to retrieve data from number of tables which effects the performance of the database.
2. Maintenance cost of relational database is high as it requires a lot of storage capability.
  
RM1*** posted at 9/14/2015 2:12:33 PM
1) What are the most important criteria to be a successful framework (or logical data model) to organize data?
The fundamental use of logical data model is to store and retrieve information from the system in a very efficient way without any error, this framework should be independent of any technology we use to store, retrieve and manage, should be standardized.
To put them in points
i. Data or the information stored according to business requirements should be well organized and structured
ii. The whole framework should be efficient to the ease of use, retrieving and managing.
iii. It should be properly normalized, without any duplication of records or event attributes/ (any information), should avoid redundancy problem.
iv. Should be scalable and should be able to restore to the natural structure.


2) What features are common in all logical data models?
Logical data model will be able to describe the data in a very efficient way, stores and retrieves independent of how the data is implemented in database.
The main features of Logical data models are:

i. Will have all the entities/records.
ii. All the entities can be accesses through the relationship among them.
iii. All the attributes of each entities are given in a efficient way without redundancy.
iv. Every entity will have a primary key which is unique different instances.
v. The relationship with the different entities are described (foreign key)
vi. Entire database is normalized and easy to use.


3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
The advantages of relational model are:
i. Compared to other database model every less redundancy.
ii. Due to less redundancy and duplication we can design the most efficient model
iii. Ease of use, quick access to huge database, maintenance and corrections are easy.
iv. As we can maintain different entities access to different entities can be restricted separately or for the whole database so we can have a good data security implementation.
The advantages of relational model are:
i. This model is not completely capable of handling extremely large and diverse data like bigdata.
ii. As the complexity of the model grows the performance of the system gets affected.
iii. Having huge number of tables/entities and their relationships and increased complexity can involve high maintenance cost to it.
  
BLU*** posted at 9/14/2015 1:40:54 PM
a. The logical data model should be able to store and retrieve large quantities of data easily.
Model can be able to implement independent of hardware and software requirements. Queries should be able to run on the whole database rather than one record at a time. Logical model should be able to store complex data types. Model should have also support high security.
b. All the models store data as a collection of records. In all models, records were connected to one other some way.
c. Advantages of Relation Model.
a. In Relation model records are connected by sharing common columns, which is a very effective to retrieve data.
b. Independent of hardware and software requirements
c. Data is stored in its natural form.
d. It provides high-level non-procedural language to access data.
d. Disadvantages of relation model.
a. As the number of tables, increase the complexity of the model increases.
b. The cost to setup and maintain a relational database increases in proportion to the size of data. If we are storing confidential information then we need to take security measures, which further increases the cost.
c. Relational database can only store simple data like numeric, characters etc… For storing complicated data like pictures, we need special databases.
  
LAN*** posted at 9/14/2015 1:06:39 PM
1.Data should be well organized and structured, less redundancy. Data should be organized and also easily accessible, so that it can be easily evaluated. To properly access the data correct connections should be used between the fields. Ease of data retrieval should also be provided.

2.Interconnection between data by using primary key and foreign key. Each type of data model contains a set of records and record set should be a collection of attributes and each has a single data value. Records must be complete and reliable to ensure data integrity. Data will be well organized and normalized.

3.Advantages:
1.It is easier to navigate(automatic navigation) than other relations model.
2.Hardware/software compatibilities.
3.Relational model links records by sharing common columns

Disadvantages:
1.Relational model setup is expensive if an organization is using different model.
2.Sequential search cannot be done in order to get correct data.
3.Complexity to store large chunks of data is another drawback.
  
SK1*** posted at 9/14/2015 12:54:58 PM
1)what are the most important criteria to be a successful framework (or logical data model) to organize data?
A Logical Data Model is a complete representation of data requirements and the structural business rules that govern data quality in support of project’s requirements. A good Data model is created by thinking about future and current business requirements. A logical data model should contain all the required entities, attributes, key group and relationships that represent business information. The most important criteria for successful framework is to make sure that data is well organized and well structured. Moreover data should be easily accessible, high structured and error free removing the redundancies and duplication. Database should be less complex.
2)What features are common in all logical data models?
A good logical data model should contain all the required entities, attributes, key group and relationships that represent business information. In addition to these data needs to be organized and well-structured removing the redundancies. The feature which is among all the data models is that data is represented by a group of similar entities which are connected and have relation among them. All the Data models are organized into records using attributes which are unique which can be used to access the database.

3)What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
Logical data models are easy to understand.
A logical data model helps us to visualize the activity of business and ability to access large amounts of data
A logical data model helps us to increase the maintenance speed and ease of transition to new technologies
Disadvantages:
Maybe difficult to modify
Not easy to spot errors
Does not have fine details
Very costly and Time Consuming
  
AR1*** posted at 9/14/2015 12:28:00 PM
Question 1:

These are few important criteria I think for a successful Logical Data Model:


1. It should reduce redundancy.
2. It should be User friendly. Lay should be able to understand it.
3. It should be easily accessible.
4. It should take less memory.
5. Maintaining data should be easier and it should very effecient and robust.
6. It should be independent of hardware and storage information.

Question 2:

1. Storing Data, Retrieving Data.
2. Every Column/Attributes will have one data.
3. All data Model will allow normalization.
4. Define Entity and relationships between them.


Question 3:

Advantages:

1. Data can be stored only once which means; It is simple to edit things on this Logical Data Model and can be stored in a better way.
2. This kind of data model can also be protected with a password/encryption to hide data or the complete table and given different kind of permissions to

view certain things only.
3. It can handle complex data.
4. Unlike Network and the Hierarchical Data model, Relational data model links records by sharing the same columns.
5. It is a means of natural structure and any data/record/entity can be managed at any time.


Disadvantages:

1. It is more costlier or expensive than other data models to handle.
2. As the complexity or the toughness of the data model increases, the expertise level to handle it also increases, this it needs an database expert to

handle it.
3. There has to be a Unique key in the tables, whithout which it won't respond to the queries.   
UDA*** posted at 9/14/2015 11:11:47 AM
Question - 1
A database is a set of records well organized by a framework or a logical data model. The most important criteria for a successful framework are
1. Records must be related or connected and easily retrievable.
2. Easily navigable from one record to a related record.
3. Minimal data duplication
4. Scalable and maintainable

Question - 2
1. Identifying Tables, Attributes and Primary Keys
2. Determining all entities and the relationships among them
3. Specifying Foreign Keys
4. Performing Normalization to minimize redundancy

Question - 3
Advantages –
1. As the data is not duplicated unlike Hierarchical model, we can optimize data storage
2. The tables are logically connected and offer Easy Data Navigation and Retrieving
3. Flexibility and Ease of use as the data can be easily stored and updated
Disadvantages –
1. When the number of tables and relationships among them increase, it affects the performance of the database in retrieving the data
2. Inability to cater for the needs of Big Data

  
PV2*** posted at 9/14/2015 11:09:13 AM
Question 1
1. Organizing large amounts of information by sorting and cataloging in one place, restoring its natural structure, reducing the possibility of inconsistent data, showing least redundant relationships
2. Validating the model, fulfilling the change model strategy, preserving data independence i.e; if a customer changes his address, them the model should show the connection between ‘customer’ and ‘address’
3. The increased ease and comfort of being accessed by everyone, from customers to respective stake holders.
4. Communicating on a business front to ensure it meets all the business requirements
Question 2
Common features in all logical data models are:
1. Data being stored, structured, related, and is a collection of records.
2. This data is retrievable and entities are related to deal with the carnality within relationships
3. Can store any kind of metadata
Question 3
Advantages:
1. Viable, secure, commercial-potential product.
2. Can create new markets for technology and has wide scope for innovation
3. Increasing the ease of accessing multiple types of information with a high level automatic navigation.
4. Provides a basis for high level data language, yielding high independence between programs and machine representation.
Disadvantages:
1. High cost of maintenance.
2. Time-to-market (TTM), which is an important factor in industries where products get obsolete, turns out to be a critical factor with this kind of technology.
3. A continuous pressure on researchers for advanced technology.
4. Complexity directly proportional to performance
  
PV2*** posted at 9/14/2015 11:08:38 AM
Question 1
1. Organizing large amounts of information by sorting and cataloging in one place, restoring its natural structure, reducing the possibility of inconsistent data, showing least redundant relationships
2. Validating the model, fulfilling the change model strategy, preserving data independence i.e; if a customer changes his address, them the model should show the connection between ‘customer’ and ‘address’
3. The increased ease and comfort of being accessed by everyone, from customers to respective stake holders.
4. Communicating on a business front to ensure it meets all the business requirements
Question 2
Common features in all logical data models are:
1. Data being stored, structured, related, and is a collection of records.
2. This data is retrievable and entities are related to deal with the carnality within relationships
3. Can store any kind of metadata
Question 3
Advantages:
1. Viable, secure, commercial-potential product.
2. Can create new markets for technology and has wide scope for innovation
3. Increasing the ease of accessing multiple types of information with a high level automatic navigation.
4. Provides a basis for high level data language, yielding high independence between programs and machine representation.
Disadvantages:
1. High cost of maintenance.
2. Time-to-market (TTM), which is an important factor in industries where products get obsolete, turns out to be a critical factor with this kind of technology.
3. A continuous pressure on researchers for advanced technology.
4. Complexity directly proportional to performance
  
PRA*** posted at 9/14/2015 11:00:51 AM
1)What are the most important criteria to be a successful framework (or logical data model) to organize data?
•The data should be complete and error-free. Moreover, you choose the data which is relevant from the available data.
•The framework links a collection of records.

2)What features are common in all logical data models?
•Every attribute will have a single value for itself.
•All the logical models have a structured set of data. But organization of the data would be different than each other.

3)What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
•The relational model links records by sharing common column which is not possible for hierarchical and network models. Therefore, it stores the data in a very systematic way.
•It describes data with its natural structure. Therefore, querying becomes simple in relational database.
•It provides data independence from hardware and storage implementation.
•It provides automatic navigation and non-procedural language to access the data. The programmer can perform the entire data set in single operation. In other words, relational databases are but one way of accessing the multiple types of information computers can handle.
Disadvantages:
•It cannot handle complex data (From research of the various universities).
•Performance may be affected when there are many entity-relationships.   
VD2*** posted at 9/14/2015 10:54:58 AM
From the above document I understood that
1. The most important criteria for framework to be successful is make sure all the data is well organized and well structured. Secondly, Accurate data should be easily accessible. We have to make sure the redundancy of data should be eliminated and also consistent data should be maintained. Lastly, This framework should meet all the business requirements.

2. Coming to features which are common in all logical data model, i understood that data here is formed by grouping similar entities together. These entities have something called single valued attributes which represents their features. Secondly, the data should well structured. Lastly they allow normalization.

3. Advantages of RDBMS:
* Duplication of data can be overcomed.
* Data can be understood with ease because it is well structured.
* Security of data is high.
* Data retrieval is simpler compare to other data models.
* Redundancy is avoided over here. So it increases the efficiency of the system.

Disadvantages of DBMS:

* The cost is high for setting up and maintaining RDBMS
* Large amounts of data can make the system complex and slow. It becomes hard to retrieve data at that moment.
* Unstructured data can lead the present model design fail.   
VD2*** posted at 9/14/2015 10:49:41 AM
From the above document I understood that
1. The most important criteria for framework to be successful is make sure all the data is well organized and well structured. Secondly, Accurate data should be easily accessible. We have to make sure the redundancy of data should be eliminated and also consistent data should be maintained. Lastly, This framework should meet all the business requirements.

2. Coming to features which are common in all logical data model, i understood that data here is formed by grouping similar entities together. These entities have something called single valued attributes which represents their features. Secondly, the data should well structured. Lastly they allow normalization.

3. Advantages of RDBMS:
* Duplication of data can be overcomed.
* Data can be understood with ease because it is well structured.
* Security of data is high.
* Data retrieval is simpler compare to other data models.
* Redundancy is avoided over here. So it increases the efficiency of the system.

Disadvantages of DBMS:

* The cost is high for setting up and maintaining RDBMS
* Large amounts of data can make the system complex and slow. It becomes hard to retrieve data at that moment.
* Unstructured data can lead the present model design fail.   
JN5*** posted at 9/14/2015 10:48:03 AM
1) What are the most important criteria to be a successful framework (or logical data model) to organize data?
• Navigation should be easy. Should be able to navigate to any record with few simple lines of Query code.
• Should be less data redundant
• Should be highly structured
2) What features are common in all logical data models?
• The data in a logical model is structured. It is collection of raw facts.
• Each table has records and each record has attributes and they are single valued

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?

1) It provides a means of describing data with its natural structure only-data independence from hardware and storage implementation and
(2) Automatic navigation, or a high- level, nonprocedural language for accessing data
  
KB1*** posted at 9/14/2015 10:29:54 AM
1)
To be a successful logical data model, it should be
-Well organized
-Less redundant
-Having only relevant attributes(no junk)
-Have only single valued attributes
-Having the relation established between the entity sets
-Be able to identify each entity set with a unique identifier

2)
The common features are:
-All the data models are intended to maintain the data or store the data with minimum possible redundancy
-All the models aim to store the data for the future retrieval
-The data models are independent on any particular technology
-The data models are described in common business language

3)
The advantages are:
-Data redundancy is very less
-Independent of the hardware and storage implementation
-Can operate queries in parallel on a single data set
-More efficient in storing the entities and establishing relation between them
-It uses high level, non procedural language to access data
-Could navigate the whole data set from any point in the data set

The disadvantages are:
-System implementation would be costly
-Complex and time consuming to implement
-Frequent maintenance is required
-Conversion from legacy model to the relational model would be a Herculean task   
AR1*** posted at 9/14/2015 10:11:33 AM
1.The most important criteria to be successful Framework to organize data-
a.Data should be well organized and well structured. b. Accessbility of the accurate data is one of the most important feature. c. An attractive interface to represent the data and user friendliness of data makes it more approachable. d. Redundency od data shouldn't be there. e. Consistency and Durability of the data should be maintained.
2.What features are common in all logical data model :
a. Strong, structured, well integrated and accurate data records which can be easily retrieved. b. Single valued attribute and properties should be maintained.
3. Advantages and Disadvantages of Relational model :
Advantages: i> Easily retrieved, High accuracy & Secured data. ii> Data independence from the hardware and storage system. iii> Efficient storage and long time durability is possible.
Disadvantages: i> Hard to understand sometimes. ii>High maintenance cost. iii>Need lots of space in hard drive. iii> Retrieving data isn't easy.

  
SIN*** posted at 9/14/2015 9:57:15 AM
1) What are the most important criteria to be a successful framework (or logical data model) to organize data?
• Less redundancy in data can help in organizing data well.
• Database should be less complex to organize data.
• Addition and deletion of the data should be easy.

2) What features are common in all logical data models?
• Relationships between entities exist.
• Data attributes will have datatypes with lengths previously assigned.
• Attributes with each entity are specified.
• Proper organizing of data into records.

3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
The main advantages of relational database are:
1) It avoids duplication of data.
2) It is much easier to change the data and change data format when compared to other logical models.
3) Rapid access to large amounts of data.
4) Describing data with its natural structure only.
5) Data In-dependency from hardware and storage implementation.
6) Automatic Navigation can be provided for accessing of data.
The main disadvantages of relational database are:
1) Limitations on the field lengths.
2) Difficulty in sharing of information form one large system to another.
3) Complexity of data is much higher because multiple tables are connected through shared key values.
4)Extraction of data in relational model is slow when compared to other logical models.
  
RAY*** posted at 9/14/2015 9:31:18 AM
1) The most important criteria constructing a successful framework to organize data is:-
* Data should be well structured such that it reflects the complete information with correctness.
* Well organized data is required to make data easily manipulated and efficiently maintained.
* Data redundancy must be reduced.

2) Features that are common in all logical data models:-
* All logic data models are conceptually simple.
* Entities and its relationships are maintained.
* Detailed structure of entity is explained like specifying the attributes and keys.
* Normalization’s can be performed at this level.

3) Advantages and Disadvantages of relational model:-
Advantages:-
* Conceptually simpler than other data models.
* Ease of understanding the data.
* Data can be manipulated easily without disrupting the whole relation.
* Easier to maintain security.
* Duplication of data can be avoided.
Disadvantages:-
* Data should be well organized else the ease of design can lead to bad design.
* If the entities between the relationships increase then the ultimate design of table complexity increases ultimately processing can be reduced.
  
MAN*** posted at 9/14/2015 9:28:00 AM
1. What are the most important criteria to be a successful framework (or logical data model) to organize data?
1) Data must be well organized and stored in a logical structure in order to be retrieved.
2) Records must be connected from the one you can navigated to, and related the one to be retrievable and useful.
3) No unnecessary redundancy.
2. What features are common in all logical data models?
1) Data independence from hardware and storage implementation.
2) Ability to naturally describe data.
3) Automatic navigation, or a high-level, nonprocedural language for accessing data.
4) One record represents one single value.
3. What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
1) Standardized two-dimensional table structure allows rapid access to large amount of data simultaneously rather than sequential navigation through leveled, defined link and pointers.
2) Different tables are related by common columns with shared key. It is easy to understand and use
3) The ability to specify single operations that would be performed across the entire data set Instead of processing one record at a time .
4) The ability to control access security.
Disadvantages:
1) It doesn’t work well for unstructured data,
2) It has difficulties to handle complex data and affects its performance.
3) Higher cost of maintenance.
4) Its performance depends on the experience of database designer
  
RK8*** posted at 9/14/2015 5:05:55 AM
: 1) what are the most important criteria to be a successful framework (or logical data model) to organize data?
The degree to which the data is accessible depends on how organized and structured the data should be, how well data is connected to one another making it more user friendly. Standardized procedures and processes. All these features form the important criteria to be a successful framework which help in providing easy access to any user.
2) What features are common in all logical data models?
The main aim for all logical data models is to recognize an entity and find relationship between other defined entities. Attributes of every entity have single value irrespective of what logical data model they belong to. To achieve a structured and organized form of data for easy retrieving is common feature.
3) What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
- Most important advantage is the Independence from hardware and storage implementation.
- Redundancy of data is avoided increasing the efficiency of the system.
- Data security is optimum.
- Data can be accessed easily even to add edit or delete in the later stages.
- Complex queries can be used to retrieve different kind of data.

Disadvantages:
- High maintenance cost of RDMS
- If an already existing database system is there it makes lot more difficult to switch to RDMS.
- More data leads to more complex relations between the data which impacts the performance.
  
BG4*** posted at 9/14/2015 2:56:03 AM
1.) What are the most important criteria to be a successful framework (or logical data model) to organize data?

Most important criteria for a successful framework is:

Data should be independent of hardware and storage implementation
Data should be well organized
Ease of accessibility
Data redundancy should be less and can be easily retrieved
 2.) What features are common in all logical data models?

Common features across 4 data models are they have well organized structured data, no redundancy, attributes, entities and relationships.

3.) What are the advantages and disadvantages of the relational model as opposed to other logical models?

Advantages of relational model
High Security
Organized and efficient storage of data and ease of retrieval
No dependency of data on hardware and storage implementation
Disadvantages of relational Model

Increase in the size of data increases the complexity thus increasing the complexity in retrieving data.
High cost involved in maintaining the data.   
HAR*** posted at 9/13/2015 11:48:28 PM
1)Criteria for a successful data model:
*The data has to be well organized and standard.
*The structure has to be well integrated to carry out the transactional tasks efficiently.
*A robust model has to be designed.
*A user-friendly operational interface

2)Common features of data models:
*All models hold a well integrated collection of data called records.
*Each record contains a set of functions and attributes having only a single data value.
*Every model holds a transaction system for data storage,retrieval and alteration.

3)Specific Advantages:
*Automatic Navigation across the entire data set.
*Usage of high level language to handle data.
*The natural and understandable representation of the data, in the form of tables.
*Data is independent of hardware and storage implementation.

Disadvantages:
Large volumes of data have significant impact over the performance of the system. The schema gets more complex as a result of which the processing time increases considerably.   
MH1*** posted at 9/13/2015 10:45:57 PM
1) The most important criteria to be a successful framework to organize data is to present and store the data in an organized manner, and user friendly way. The data should also be easily navigable for retrieval, and data redundancy should be achieved.
2) The most common feature in all the logical models are
a. Records are connected to one another.
b. Data is navigable.
c. Data redundancy is achieved

3)
Advantages of relational database model:
a. Organized: The organizing of data into tables, rows and columns simplified the usage
and understanding.
b. Navigation: The navigation to linked records became easier since the records
in the tables share the same unique column.
c. Redundancy: Data normalization can be achieved and all the redundant data can be reduced to make the database more optimized

Disadvantages:
Performance of the database is sometimes effected if there are large
number of tables in a complex database system. A complex database might also use complex queries to extract data, thereby impacting the performance of the database.   
VV2*** posted at 9/13/2015 10:12:03 PM
1) - Defined scope/purpose of model.
- Well Organized/Structured data.
- Readily Accessible data once stored.
- User-Frienldy; Hassle-free;
- Documented procedures for database implementation; A featured training on the developed database would help the users.


2) Any logical data model would store the data as a collection of records where each record allows only a single attribute to store. All logical models are developed in a way that it can separate data from hardware and storage implementation. Retrieval time and accuracy may vary among all the logical models.

3) Advantages:
As the data is stored in the form of tables (Columns and rows), revisions/updates to data could be simpler.
If at all I want to hide some specific information, I could simply hide the table for a specific user and thus improving security.
Disadvantages:
I think the major disadvantage is performance. As the data is linked through common records, increase in data increases the links between records and thus makes system complex and affects performance
  
SWE*** posted at 9/13/2015 10:07:50 PM
1. Criteria to be a successful frame work.
Accessibility of data is the most important criteria for a frame work to be successful. An organized structure of data helps in retrieving data and manage it at faster pace.
2. Common features in all Logical data models.
The common features among all the data models is that data is represented as a group of similar entities clubbed together. Each individual entity has its own set of features called attributes having one unit value.
3. Advantages and Disadvantages of Relational Data model.
Advantages:
• Make the data easy to understand.
• Joining of the tables helps in retrieving all the necessary information of a particular entity from the entire database.

Disadvantages:

The relational data model could be complicated if there is a large set of data having multiple tables interconnected which might lead to confusion.
  
DV3*** posted at 9/13/2015 9:44:00 PM
1)What are the most important criteria to be a successful framework (or logical data model) to organize data?
The Most important criteria are that:
- Data should be represented by the collection of records. Each record is collection of fields.
- Each of field should contain one and only one data value.
- Proper connection should be made among records to properly access the data.
2)What features are common in all logical data models?
The features that are common in all logical models are:
- Each logical model has records.
- Records are connected to each other i.e., have relationship among them.
- There is a way to retrieve the data from the records in each logical model.
- Each record has a collection of fields containing only one data value.
3)What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
- Rapid Access to Large Amounts of data
- Ensures Quality of data
- Maintains privacy of data
- Avoids duplication of data
- Data can be extracted from various tables by running one SQL query
Disadvantages:
- When compared to Hierarchical model the understanding of relationship between records is tough task. You can’t understand the relationship of large data by just looking at the tables.
- Needs more tables to store the data which can be an issue if we are dealing with large data and the data access also needs more time.
- Huge no. of tables also effects the performance of the system.
- Maintainance of databases costs high   
KAR*** posted at 9/13/2015 7:25:01 PM
Qno1) What are the most important criteria to be a successful framework (or logical data model) to organize data?
The most Important significance of a logical Data model is to present the data in a user friendly or in a easy interactive
manner. since database is all about the data storage and data retrieval, both of these process should be done
easily with any logical data model.
As stated in the given article, data independence from hardware and storage implementation,automatic navigation
are the important criteria for logical model to be feasible and user friendly.
Data collected should have an organised structure.Since organized data consists of specific attributes which clearly define about the record in the data base table.
so on a whole the most important thing for any framework to be successful is to provide easy access to any user.

Qno2) What features are common in all logical data models?
The most common features in all most all the logical databases are: Data Independence,automatic navigation, tables and their Relationships.
In all logical databases data is well organised into records, using attributes which are specific and unique.
With the help of these fields these records can be retrieved easily by any user.

Qno3) What are the advantages of the relational model as opposed to other logical models?
The advantages of a relational model are:
1) Data independence from hardware and storage Implementation.
2) Automatic Navigation
3) No data duplication
4) Ease of Data retrieval
5) No inconsistent data.
6) High data security.

The Disadvantages are as follows:
With the increase in number of relationships between tables the complexity also increases.
It increases the time taken to retrieve any record from the database.If the amount of data increases storage issues also raise.
It in turn increases cost for maintaining the database.   
SHU*** posted at 9/13/2015 7:09:03 PM
1) A set of Data organized in a fashion represents Logical Data Model which is a representation of Data Requirements and structural Business rules. Data is a collection of records which indeed is a collection of attributes and properties having unique data and logical connection between one another. The link should be so that Data can be easily accessed by minimum time spent upon searching.

2)The features common in all Logical Data Models is that -
- Organized and consistent Availability of Data
- Avoidance of Redundancy
- Data re-use and sharing
- Querying and Retrieving through Complex queries
- Single-valued attributes of each entity

3) Advantages of Relational model -
- Flexibility - Tables are interlinked so it is flexible to extract data
- Highly Secured
- Data In-dependency - achieved more easily with Normalization
- Possibility of responding to complex queries based upon relational Algebra and Calculus.

Disadvantages -
- Performance is affected if the tables having relationships are large.
- Data Complexity
- Hardware Performance - DB with external Data sources may need more powerful servers to return results within an acceptable time.   
NK6*** posted at 9/13/2015 7:08:25 PM
1. What are the most important criteria to be a successful framework (or logical data model) to organize data?
The most important criteria to be a successful framework to organize data is to maintain well defined relations between the data tables, maintain the ACID properties (Atomicity, consistency, Isolation & Durability) during the data transactions and independence of data from hardware and storage implementation.
2. What features are common in all logical data models?
There are 4 major types of logical data models: Hierarchical data model, Network data model, relational database model and object oriented database model. The data is generally organized in entities, represented as a collection of records. It comprises of the attributes, properties, fields, etc. Each record carries information of various fields.
3. What are the advantages and disadvantages of the relational model as opposed to other logical models?
Advantages:
- The relational model defines the data with its natural structure, independent of hardware and storage implementation.
- Compared to other data models it offers more flexibility in terms of retrieving the data i.e. it can process multiple records (data set) at a time, as the records are related in the relational database.
- Relational databases generally follow ACID properties. I.e. Atomicity, consistency, Isolation and Durability. The properties make the data transactions more reliable.
Disadvantages:
- Data is saved in multiple tables and these tables are related which results in very complex data environment.
- These are very expensive to setup and maintain.
- If huge number of tables accompanied by relationships lead to a complex environment then it will affect the performance of the overall system.
  
MAR*** posted at 9/13/2015 5:58:27 PM
1) The significant criteria for the logical model to be successful is to organize or arrange the data in a manner so that a user can retrieve a record or information in the most feasible or in a user-friendly manner. There should be less burden on users to retrieve the data. And as found from codd's work in the above passage "data independence from hardware and storage implementation" , "automatic navigation" are the important criteria for logical model to be feasible and user friendly. the main importance lies on the relating and linking the organized data and its entities for the easy retrieval of data.

2) The common factors and features in all logical models are they are all well organized and are having structured data. In all of the models data is collection of records and each record is a collection of fields and has only one data value. but the only difference is in the way they got organized and linked.

3) Advantages of relational model

. Data is stored only once, which will avoid the problem of duplication.
. Increases security.
. Data independence from hardware and storage implementation
. Automatic navigation

Disadvantages of relational model

. Effect on performance- As the size of the data increases it becomes complex to retrieve data.
. As the complexity of data increases, the skill and expertise required for the users to manage and retrieve data also increases.   
BHA*** posted at 9/13/2015 5:30:45 PM
1) What are the most important criteria to be a successful framework (or logical data model) to organize data?
A framework or a Logical data model is a graphical representation of the business rules and requirements. The logical data Model has entities, attributes and the relationships involved in the business.
For a Logical Data Model to be successful:
- The presence of data in addition to the actual data which may cause errors to the business should not be present. This helps in preventing inconsistencies in data.
- The data should be properly organized and saved.
- The Logical Data Model should be reviewed and approved by the business Managers.
- Also, the names used in the Logical Data Model should represent the business.
- Availability of Data.
- Easily Accessible.
- The queries should return appropriate data accurately.
2) What features are common in all logical data models?
- Every data Model has data independence.
- No Redundancy
- Availability
- Entities, Attributes and Relationships.
- Easily returns the required data.
3) What are the advantages of the relational model as opposed to other logical models?
- Efficient Storage
- Complex queries can be used easily
- Data security is high
- Easy to changes data and data format
- Avoids inconsistent data
- Easily accessible and Easily understood
4) What are the disadvantages of the relational model as opposed to other logical models?
- If the number of entities between which relations are established is high, it may lead to poor performance.
- Storage Issues
- Implementation and handling the data is difficult with more data.
- Cost.
  
SIN*** posted at 9/13/2015 4:05:35 PM
1. criteria for a successful logical data model:

* A successful logical data model should Understand the requirements and enable effective and efficient data storage such that the data is readily accessible.
* Should avoid data redundancy making it easy to retrieve
2. Every Logical data model has organized data which is a collection of records.Each record has its attributes and is single valued.


3. ADVANTAGES

* Avoids data redundancy
* able to carry out the complex queries
* performing any changes to the data is easier
* more secure

DISADVANTAGES

* Involves more tables leading to data complexity
* Difficult to switch from old logical data model
* Incase of complex queries, experienced developers may be required.
  
ANI*** posted at 9/13/2015 4:02:20 PM
Question 1:
• Data should be well organised to retrieve the data whenever necessary.
• Flexibility in accommodating data( small or large data)
• Should be independent of technology.


Question 2:
All logical data model contains:
• entities and their relation ships
• Attributes for each entity.
• Organized data.

Question 3:
Advantages of Relational Model compared to other logical Models:
• Independence from hardware and storage implementation
• Ease of access to the data compared to other models because of tables, rows, columns and relations between the tables.
• Flexibility in retrieving the data from different tables using operators.
• Secured retrieval of data can be achieved by introducing authorization levels.
Disadvantages:
• Non usage of optimized query to retrieve data lead to performance issues.
• Retrieving complex information from big data needs high level expertise.
  
JBO*** posted at 9/13/2015 3:17:24 PM
Joshua Boley
1.)The most important criteria for a successful framework

* Strong structure to organize data
* Easily accessible data after storage
* Clear standardization of processes and procedures
* Support from industry, community, and researchers

2.)What features are common in all logical data models?

Every logical data model has data represented by collections of records. Where each record is a collection of fields (attributes, properties), each of which contains one and only one data value. Also the ability to store and retrieve organized data in a structured manner.

3.)What are the advantages and disadvantages of the relational model as opposed to other logical models?

Advantages
* Rapid access to large amounts of data
* Provides a means of describing data with a natural structure
* Data independence from hardware and storage implementation
* Automatic navigation, or high-level, nonprocedural language for accessing data

Disadvantages
* In ability to handle complex data
* Time for return of results in “Big Data” sets
* Cost to implement in changing over from old systems
  
FAT*** posted at 9/13/2015 2:48:13 PM
1) The most important criteria to be a successful framework:
-Data should be well organized on related records.
-Records must have a unique identifier.
-Data should be easily navigated by users.
2) The common features in all logical data model are:
- All data are stored on records
-All records are related either by a pointer in Network and hirarichacl model or by sharing common data in relational model.
A record is a collection of attribute , that has one single value.
3) The advantages of the relational model:
Data independence from hardware and storage implementation
Automatic navigation, or a high- level, nonprocedural language for accessing data.
A programmer could use the language to specify single operations that would be performed across the entire data set.
  
SUR*** posted at 9/13/2015 12:55:21 PM
The important criteria for a logical model to be successful is, it should be structured properly . It should be organized in a perfect way such that it can handle huge amount of data, data with many types and should be easily retrievable for data analysis.
The common features of all logical data models is that they store the data in a structured manner. But the way they store the data and how they are organized are different in each data model. All the data models take a single value for each attribute.
Advantages :
1)Using normalization structure data independence can be achieved easily.
2) Data extraction is very easy for the user and also data can be linked to form different tables according to the user needs.
3) By providing authorization to sensitive attributes data security can be increased.
4) By using structured query language database can be easily approached

Disadvantages

It is very difficult to handle huge amount of data as it becomes complex in building relations.
2) There is a lot of load on the system while retrieving data and running complex queries.
  
KR6*** posted at 9/13/2015 12:29:05 PM
1) The most important criteria for framework to be successful is :
* It should meet the business requirements
* The data should be well organized and normalized.
* Data redundancy problem should be eliminated.
* Data should be easily approachable and retrievable.

2) All logical data models include
* Entity and relationships between them.
* Attributes for each entity are specified and have single value
* Data is well structured
* All models allow normalisation.

3) Advantages of RDBMS :
* Data security is high
* Data is efficiently stored
* Overcomes duplication of data.
* Data can be extracted from various tables by running one SQL query.

Disadvantages of RDBMS :
* Finding relations among different attributes is difficult and time consuming.
* Advances in complexity of big data is another drawback RDBMS has.
* The cost of setting and maintaining RDBMS is high.


  
SWE*** posted at 9/12/2015 9:15:58 AM
Sweekar Deshmukh

1) Criteria for a successful framework,
• Ability to store large amount of data in an organized way so that it can be
fetched easily and quickly whenever required.
• Independence of data from software and hardware (Codd’s research).

2) All logical data models are aimed towards storing data in an organized way,
without duplication, with ensuring interconnectedness between different fields
making processing of data faster.

3)
Advantages:
• Ability to store data in an organized way facilitating quick fetching and
processing.
• Ability to run batch queries on entire dataset.
• Reduction in redundancy by sharing common columns in multiple tables.

Disadvantages:
• Limitations while handling complex data.
• Use becomes difficult while handing large amount of unstructured data.
• Inability to store increasing amount of “Big Data”.
  
ZEE*** posted at 9/11/2015 12:19:09 AM
1) A successful framework should have interrelated records such that it forms a meaningful relationship. Also Data should easily be extracted and accessed by end users.

2) Every Logical data model has Collection of records. It has a single value. Also it conveys same information irrespective of what data model is used to organize data.

3) Following are the Advantages of Relational Model over other Logical models:
a) Relational model has High speed access to Large amount of data at the same time.
b) High-level, non navigational, data-independent interface to many users simultaneously, with high integrity and robustness.
c) Data is independent from hardware and storage implementation.
d) Data response to query by SQL is very easy in relational approach than for data organized through other models the query language either becomes complex.

Disadvantages:
a) As the data advances the complexity of relational data bases increases and may need some advance training to users which makes this model expensive.
b) Many of the operations involve sequential searches to find the right data to satisfy the specified relation. In such case hierarchy or Network model would be more appropriate.   
SK2*** posted at 9/10/2015 4:52:24 PM
1.Framework is used to organize data. Thereby a successful logical data model accurate data grouped into sets with well defined relationships between them. They must also contain only relevant information.
2.The most common feature among the 4 models are that they all store data, data is retrievable and at a time, one record can have just one data value.
3.a.Advantages
- In the Hierarchical Model, lower level data cannot be retrieved if the first (highest) tree node data is not known and cycles of linked data which is not supported. In contrast, with Relational model you can retrieve data at any level and they have cycles of linked data.
- In Network model even though linking of data in cycles is allowed, the records continue to remain linked through pointers. From my undergraduate, the disadvantage of pointer system of storage is if we delete a record then the pointer can continue to store junk or null values if not handled properly. This might lead to storage issues in long run. In Relational model data is stored using tables which allows easy creation and manipulation of data.
b.Disadvantages
-It can get quiet complex and time consuming to remember all the relationships and come up with simple yet effective structure for data. But with tree model all you need to remember is a parent node under which all data can be stored.
-By sharing columns we might have to store data in multiple places in the Database.
  
ETW*** posted at 9/9/2015 4:54:08 PM
Eric Weber

1. In order to be a successful framework, the data must be well-organized, easily accessed and searched, and correctly related to other data.
2. Every logical data model contains collections of records which contain fields, which are represented by one single value.
3.An advantage of the relational model is that related data are grouped together for easy access. It also has a huge advantage in that you can perform actions across an entire data set rather than single pieces of data. a disadvantage of this model is how difficult it is to switch to this system when you already have a different model in place.   
AND*** posted at 9/9/2015 3:13:11 PM
Andrew Genet

1. The most important criteria to be a successful framework to organize data would be a well-organized set of records where all the records are connected so that it’s easily navigated from one to related ones.
2. Common features in all logical data models include records, correct and organized data, with some form of navigation. The records must be complete and accurate to ensure data integrity.
3. The advantages of a relational model include being able to access data across an entire data set. A rational model uses shared columns for efficient data use. The disadvantages may include implementing this model in a setting where there is a pre-existing data model already in place.
  
JOE*** posted at 9/9/2015 7:09:10 AM
by Joseph A. Gogins

1) The most important criteria to be a successful framework to organize data are to have data independence from hardware and storage implementation and to have an automatic navigation, or a high-level, nonprocedural language for accessing data. This method would save time creating the database.

2) The features that are common in all successful logical data models are records, well-organized data where the records are connected without any unnecessary redundancy, accurate, complete, and reliable.

3A) The advantage of the relational model as opposed to the other logical models is that the relational model links records by sharing common columns. This means that instead of processing one record at a time, a programmer could use the language to specify single operations that would be performed across the entire data set (Codd 1960).

3B) The disadvantage of the relational model as opposed to the other logical models is that the relational model would be difficult to implement and expensive if a company has already been using the other logical models.   
LLI*** posted at 6/15/2015 11:13:09 PM
by Chad Kidder

1. In order for a database model to be successful, according to Codd’s research, is to provide a means of describing data using natural data structure, while keeping the data independent of hardware and software restrictions and/or demands. These concepts are the founding principles of a relational database.
2. Each type of data model contains a set of records, which are themselves further described by a set of fields, usually populated by a set of characteristics, usually alpha-numerical, numerical or symbolic in nature. Each characteristic should contain only a single value.
3. The relational data model, in comparison to the hierarchical or network data models, allows for the best flexibility in terms of framework, hardware/software compatibilities, and advance data accessing and information construction. Using this modeling theory, individuals, companies and governments alike have been able to more easily utilize more data for creating invaluable information and advancing their knowledge in a particular sector (e.g. Data mining industry and the “big data” movement). Historically, one of the downfalls to relational model was the already established programs and investments into the hierarchal and nodal logic data models by government and other corporations. Not only was relational data structuring a new model, it was a change in culture of organizing data. Personally, a relational model can also be difficult to visualize on screen or paper, especially when there is not a lot of data to be correlated. Something as simple as a small businesses’ organizational structure, could lack the correct visual information to convey the proper information, if in a raw relational data table form.
  
LLI*** posted at 6/15/2015 9:44:45 PM
by Kaitlyn Becka

Based on information learned in class, relevancy, understandability, consistency, complete, free-of-error, completeness, and timeliness are several important criteria for data quality and the organization of data.
All logical data models are characterized by a collection of records and each record provides specific attributes and properties. Each field is only allowed one data value to be recorded which is the same feature for every type of logical data model. Advantages of the relational model are that it links records by sharing common columns which allows all of the information in the tables to be connected. Information in a relational model is explained naturally without covering up any information for relationship reasons. Disadvantages are that the relational model is not a tree structure or use pointers to connect records. The relational model does not link a collection of records or allow for loops in the connections.   
JOE*** posted at 6/15/2015 5:29:27 PM
1)In my opinion the most important part of any system is the data integrity. without this fundamental aspect there are no relationships, or analysis of data that will give relevant and trustworthy insight.
2)main features that all logical data models contain sets of data, usually organized in a table. the rules and construction of these tables differs but they exist to create usable data reports.
3)relationship data models offers a more flexible and stable structure to build the database off of. this model can be maintained by let technical people which reduces the cost of operations. logical models by definition require a operator who is more advanced and capable of handling complex data structures. training and replacing this person is expensive and time consuming process.   
RK5*** posted at 6/15/2015 5:27:46 PM
The most important criteria to be a successful framework is to have precise data that is correlated and is intertwined with one another. The data needs to be correct, precise, organized, relevant, and accurate. Each data has its own value but it is also correlated with the rest of the data. Features that are common in most data is that the data has a purpose and it is somehow related to the main question. Advantages are that the data is easy to read and is correlated. The disadvantages are that the data can get very extensive and get out of hand.   
SPI*** posted at 6/15/2015 2:44:49 PM
1. In order for a database model to be successful, according to Codd’s research, is to provide a means of describing data using natural data structure, while keeping the data independent of hardware and software restrictions and/or demands. These concepts are the founding principles of a relational database.

2. Each type of data model contains a set of records, which are themselves further described by a set of fields, usually populated by a set of characteristics, usually alpha-numerical, numerical or symbolic in nature. Each characteristic should contain only a single value.

3. The relational data model, in comparison to the hierarchical or network data models, allows for the best flexibility in terms of framework, hardware/software compatibilities, and advance data accessing and information construction. Using this modeling theory, individuals, companies and governments alike have been able to more easily utilize more data for creating invaluable information and advancing their knowledge in a particular sector (e.g. Data mining industry and the “big data” movement). Historically, one of the downfalls to relational model was the already established programs and investments into the hierarchal and nodal logic data models by government and other corporations. Not only was relational data structuring a new model, it was a change in culture of organizing data. Personally, a relational model can also be difficult to visualize on screen or paper, especially when there is not a lot of data to be correlated. Something as simple as a small businesses’ organizational structure, could lack the correct visual information to convey the proper information, if in a raw relational data table form.   
WDA*** posted at 6/15/2015 12:42:39 PM
In order to have a successful and logical data model that organizes data it must include the following criteria: accuracy, completeness, correct, organized, relevancy, precision, reliability. Each logical data model is characterized by a collection of attributes and each has a single data value. The relational data model can describe data within its original structure and by utilizing a nonprocedural language you could process an entire set of data instead of processing a single record one at a time. The relational model has had much commercial success and gained its legitimacy with the help of government funding within the technical community and IBM.   
SFK*** posted at 6/14/2015 5:00:13 PM
1) The most important criteria to be a successful framework (or logical data model) to organize data is to make sure that your info/content is correct and that the info is placed in the model in the correct spot so that the relationships can be clearly seen or the model is useless if the relationships are wrong. 2) The 2 main features that are common in all logical data models according to the second passage are: "(1) data independence from hardware and storage implementation and (2) automatic navigation, or a high-level, non-procedural language for accessing data." What I think this means is that the model has just enough needed info for the programmer to understand the relationships and what the programmer needs to do as well. 3) The advantages and disadvantages of the relational model as opposed to other logical models are: 1. Advantages according to the passage are that "It provides a means of describing data with its natural structure only” that is, without superimposing any additional structure for machine representation purposes. Accordingly, it provides a basis for a high level data language which will yield maximal independence between programs on the one hand and machine representation on the other." I think this means that the model was good in the sense that it gave the info needed while not having extra info in the model that was not needed so the programmers could clearly understand what was meant by the model. Disadvantages according to the passage are that "Within IBM, the trouble was the existing database product, IMS. The company had already invested, both financially and organizationally, in the infrastructure and expertise required to sell and support it. A radical new technology had a great deal to prove before it could displace a successful, reliable, revenue-generating product such as IMS." What I think this means is that IBM already had a successful database and did not want to spend the time or money on something new that might not work. However, once the paper about the model was published and the company saw outside views they realized the potential that the models could have.   
KBE*** posted at 6/14/2015 2:20:54 PM
The most important criteria for data quality and the organization of data are relevancy, understandability, consistency, complete, free-of-error, completeness, and timeliness. All logical data models are characterized by a collection of records and each record provides specific attributes and properties. Each field is only allowed one data value to be recorded which is the same feature for every type of logical data model. Some advantages of the relational model are that it links records by sharing common columns which allows all of the information in the tables to be connected. Also, information in a relational model is explained naturally without covering up any information for relationship reasons. Some disadvantages are that the relational model is not a tree structure or use pointers to connect records. In addition, the relational model does not link a collection of records or allow for loops in the connections.   
SMH*** posted at 6/13/2015 6:22:29 PM
1) The most important criteria will change accoring to user prefrences. Its whatever the user feels is most important. The data should be organized in a logical manner and should have connections or relationships with each other.
2)In logical data models, each record is a collection of attributes and contains only one data value.
3) in the retnetion model data is described by using its natural structure. It is not dependent on hardware or storage. It uses non-procedural language to access data and can process more than one record at a time. Single operations can be performed across the entire data base.
  
LLI*** posted at 6/13/2015 10:37:34 AM
by Kerri McMahan

The most important criteria to be a successful logical data model to organize data would be that the model is accurate, complete, correct, organized, relevant, precise, and reliable. Common features in the logical data models includes specific attributes and data is represented by collections of records. The advantages to relational model includes automatic navigation as well as data independence from hardware and storage implementation. A disadvantage of the relational model is the link of common records. I think that linking everything together by common records would end up being very complex with many records joining together in a massive clump.   
LLI*** posted at 6/13/2015 10:35:52 AM
by Nick Heimbaugh

1. The most important criteria to be a successful framework to organize data is that there has to be some sort of link between the points of data, so that the data can be accessed quickly from minimal amounts of searching.
2. Features that are common in all logical data models is that they all have storage units in order to store the information, as well as they all have an interconnectedness between the data which helps link the information together.
3. The advantages of the relational model are that it is independent of hardware and storage implementation as well as it can process many records at a time, not just one record, also it is easier to navigate then the other relations models The disadvantages of the relational model is that it was hard to convince companies to switch to this model of relation’s because they were already using different models and had already put a lot of money into those models, as well as the relational model was harder to create in a system then the other logical models.
  
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