Data Modeling Advantages

Data modeling is the process of analyzing the things of interest to your organization and how these things are related to each other. The data modeling process results in the discovery and documentation of the data resources of your business. Data modeling asks the question “What?” instead of the more common data processing question, “How?”

Data modeling asks the question “What?”

Before implementing databases of any sort, a DBA or DA needs to develop a sound model of the data to be stored. Novice database developers frequently begin with the quick-and-dirty approach to database implementation. They approach database design from a programming perspective. Because novices often lack experience with databases and data requirements gathering,

The value derived from the data model exhibits itself in the form of minimized data redundancy, maximized data integrity, increased stability, better data sharing, increased consistency, more timely access to data, and better data usability. These qualities are achieved because the data model clearly outlines the data resource requirements and relationships in a clear, concise manner. Building databases from a data model will result in a better database implementation because you will have a better understanding of the data to be stored in your databases.

Another benefit of data modeling is the opportunity to discover new uses for data. A data model can clarify data patterns and potential uses for data that might otherwise remain hidden. Discovery of such patterns can change the way your business operates and can potentially lead to a competitive advantage and increased revenue for your organization.

A data model can clarify data patterns and potential uses for

This chapter discusses data models as they pertain to individual projects or applications, but not the relatively advanced topic of the enterprise data model. Managing and maintaining an enterprise data model is fraught with many non-database-related distractions such as corporate politics and ROI that is hard to quantify.

If your organization has committed to developing and maintaining an enterprise data model you should definitely take the time to read more about the topic by consulting the books referenced at the end of this chapter and the articles at www.dbazine.com.

Data modeling requires a different mindset than requirements gathering for application development and process-oriented tasks. It is important to think “what” is of interest instead of “how” tasks are accomplished. To transition to this alternative way of thinking, follow these three rules.

Don't think physical; think conceptual. Concern yourself with business issues and terms rather than physical storage issues and DBMS