Database Modeling & Design Fourth Edition- P14 | Requirements Analysis and Conceptual Data Modeling This chapter shows how the ER and UML approaches can be applied to the database life cycle particularly in steps I through II b as defined in Section which include the requirements analysis and conceptual data modeling stages of logical database design. The example introduced in Chapter 2 is used again to illustrate the ER modeling principles developed in this chapter. Introduction Logical database design is accomplished with a variety of approaches including the top-down bottom-up and combined methodologies. The traditional approach particularly for relational databases has been a low-level bottom-up activity synthesizing individual data elements into normalized tables after carefully analyzing the data element interdependencies defined during the requirements analysis. Although the traditional process has been somewhat successful for small- to medium-sized databases when used for large databases its complexity can be overwhelming to the point where practicing designers do not bother to use it with any regularity. In practice a combination of the top-down and bottom-up approaches is used in most cases tables can be defined directly from the requirements analysis. The conceptual data model has been most successful as a tool for communication between the designer and the end user during the 53 54 CHAPTER 4 Requirements Analysis and Conceptual Data Modeling requirements analysis and logical design phases. Its success is due to the fact that the model using either ER or UML is easy to understand and convenient to represent. Another reason for its effectiveness is that it is a top-down approach using the concept of abstraction. The number of entities in a database is typically far fewer than the number of individual data elements because data elements usually represent the attributes. Therefore using entities as an abstraction for data elements and focusing on the relationships between entities greatly reduces
