Renée Taylor Consulting recommends enterprise data modeling in order to plan strategic information system development, maximize data integration, and increase data integrity across an enterprise.

What is an Enterprise Data Model?

A data model consists of a diagram composed of high-level data entities and the relationships between them, along with descriptions and examples. It is a model of the information required by an organization, and illustrates how that information is linked. The things of importance (entities) within the business, the properties of those things (attributes), and how they are related (relationships) are all depicted on a data model. When the scope of the modeling is across the entire business, the model is called an enterprise data model.

An enterprise data model is a very powerful communication tool for creating complex models using simple conventions that can be easily explained. This technique is independent of the mechanisms used to hold that information, such as paper forms or computers. As long as the business does not change, the model will remain accurate.

Benefits of Enterprise Data Modeling

Enterprise data modeling is a technique that aids in:

• Identifying related and overlapping information across multiple systems elements
• Reducing data overlaps and inconsistencies and data integrity problems arising as a result
• Creating an architecture for data interfaces and potential integration of data elements that can be mapped to database designs for future in-house IT projects and third-party purchases
• Developing a direct route to an integrated, flexible information resource based on a clear understanding of information requirements expressed as data structures, interdependencies, and common functionality
• Planning for high-quality systems that better meet the requirements of enterprise information processing, derived from business models agreed between managers, users, and developers
• Initiating working practices in the organization to support the implementation of structured techniques for systems development and the use of supporting CASE tools
• Improving productivity within IT by clarifying basic concepts at the senior management level and simplifying requirements or converging redundant development efforts
• Enabling the scoping of information requirements for major information systems efforts, such as the acquisition of financial management software, new systems developments, and longer-term IT planning to integrate information across multiple current systems