Evolution Of Data Model Essay

Evolution of data model
The evolution of data model was traced back in 1960s when the first generation of data model – File system model was introduced. File system used to strictly maintain the records and it does not have relationship between the tables. As the requirement to for managing data evolve, in 1970s, hierarchical and network model were used. These data model handle the relationship between the tables and conceptually simple. However, it still using navigational system and complex in implementation. And the change in structure requires a changes in all application program (Morris 55). The major evolution of data model happen in 1970 when “relational model was introduced by E.F. Codd of IMB in his landmark paper “A relational Model
RDBMS help to manage the complexities of physical details of data model, when users are working with data, they interact with data by using SQL (structured query language). This is the major advantage of relational model. The complexity of physical design was replaced with more intuitive and logical language. Entity relationship model is the next advancement from relational model. It proved to be an ideal database design tool with the progress in using graphical tool to illustrate the relationship diagram. There are 3 ER notation: Chen notation (introduced by Peter Chen in 1976), Crow’s Foot notation (widely used today), class diagram notation. Each of ER model has 3 components Entity, Attributes and Relationships. The increasingly complex of data lead to the new data model – Object oriented data model (OODM). An object is much like an entity, however, it contains both data and relationships. OO data model contain these components: object, attributes, class, class hierarchy, inheritance and Unified
“Normalization is the process for evaluating and correcting table structures to minimized data redundancies, thereby reducing the likelihood of data anomalies”. (Morris 191). The normalization process go through the steps and transform into higher normalization form. The normal forms are First normal form (1NF), Second normal form (2NF), Third normal form (3NF), Boyce-Codd normal form (BCNF) and Fourth normal form (4NF). In database design, the higher the normal form is desirable. However, in the real business environment, 3NF form is most the most likely ideal normal form. Another important concept in Data Normalization is functional dependence. “The attribute B is fully functional dependent on the attribute A if each value of A determines one and only one value of B” (Morris 196). Normalization process involves the detection of functional dependency and breaking the dependency into new table. There are 2 types of functional dependency are partial dependency and transitive dependency. “Partial dependency exists when there is a functional dependency in which the determinant is only part of the primary key” (Morris 196). “Transitive dependency exists when there are functional dependency such that X->Y, Y->Z, and X is the primary key” (Morris 196). The ultimate goal of the database designer is to reduce the dependency without sacrifice too much performance. Because when you create another