What Is Data Modeling?

Data modeling is the process of identifying, documenting, and implementing the data requirements for your application. This involves reviewing existing data models and processes to see if they can be reused, and creating new data models and processes to suit your application's unique requirements.

The major events in data modeling are:

• Identifying the data and associated processes (such as that sales people in the field need to see the online product catalog and submit new customer orders).
• Defining the data (such as data types, sizes, and defaults).
• Ensuring data integrity (by using business rules and validation checks).
• Defining the operational processes (such as security reviews and backups).
• Choosing a data storage technology (such as relational, hierarchical, or indexed).

It's important to understand that data modeling often involves company management in unexpected ways. For example, data ownership (and the implied responsibility of data maintenance, accuracy, and timeliness) is often challenged by new insights into what data elements should be maintained by which organizations. Data design often forces a company to recognize how enterprise data systems are interdependent, and encourages the efficiencies, cost savings, and strategic opportunities that come from coordinated data planning.

At the conclusion of data modeling, you have a complete definition and implementation of your application's current data requirements, and you have provided a strong foundation for future extensions and data reuse by other enterprise applications.