A Relational Model of Data for Large Shared Data Banks (Essay Sample)

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Reflection
Codd’s paper on "A Relational Model of Data for Large Shared Data Banks" is a proposition to make it easier for users of large data banks. This endeavor, as Codd explains is achievable by protecting such consumers from interacting with internal machine organization, i.e. how programmers organize data in a machine. Codd downplays a prompting service that can provide this information. He asserts that such a service is not a satisfying solution. The paper highlights that user-activity at terminals and in machines, programs ought not to be interfered with on altering both the internal and external data representation. This is bearing in mind the fact that changes in data representation will always happen. Codd emphasizes that changes in query, report traffic, updates, and Increase in stored information will always occur. So why the need for a new model of data for large shared data banks? In addressing this question, Codd gives a perspective of the limitations of the existing systems. He explains that the current non-inferential formatted data systems offer their users with tree-structured files that have more general network models of the data and have several inadequacies. These drawbacks include data independence, which is the independence of application programs and terminal activities from growth in data varieties and transformation in the data presentation. Secondly, existing systems have particular kinds of data inconsistencies that designers expect to be prone to troublesome even in non-deductive systems. The author advocates for this model because, besides its perceived user –interactivity ease it has several other advantages. For example, it provides a means of explaining data with its natural structure without covering over any additional structure for machine representation aims. Likewise, it provides a basis for a high-level data language to yield optimum independence between machine representation and information organization on one hand, and programs on the other hand. Additionally, the relational view model provides a concrete basis for treating derivability, redundancy, and consistency of relations. The author provides examples of this clearer perspective are cited in various parts of this paper. However, the limiting weakness of the authorship is that it fails to discuss of to implement the systems that can support the relational model. Nevertheless, Codd’s piece is quite a detailed paper that deserves further discussion.
The second article by Peter Pin-Shan Chen is on "Entity-Relationship Model-Toward a Unified View of Data”. The report proposes an entity-relationship model that can give a unified view of data. So how does Peter’s model achieve its aim? The article highlights that the model features some of the critical semantic details about the real world. It incorporates a special diagrammatic technique as a tool for the design of the database. Besides discussing the implications for information retrieval, integrity, and manipulation, the model also gives an overview example of database design and description of the model. In addition, Peter explains how to apply the diagrammatic technique. The key question emerging from the discussion is the critical essence of the entity-relation model. The paper addresses this by stating that the model provides a foundation for the unification of different views of data. These data perspectives or dimensions include the relational model, the network model, and the entity set model. Peter goes beyond analyzing the semantic ambiguities present in the model and gives possible ways in which to derive views from the model. I think the paper answers the dilemma questions that many readers would want ...