We’ve come to understand the importance of models, whether these are data, process, business or capabilities models. One of the most important models is a data model. Dr. Robin Bloor, who resides here in Texas and is the chief analyst and founder of the Bloor Group, says “the more complex the data universe becomes, the more you need to model it.” If your organization has different departments working with differing aspects of the same set of data, for example when multiple organizations are using the same data from a CRM or ERP system, then a data model can be very valuable and ultimately improve decision making.
Data models provide and communicate the definition and format for your core data. They enable us to organize variables of information in a way that helps us relate the variables to each other and reflect occurrences or applications in the real world. They facilitate and support the idea of a single source of truth.
Data models provide and communicate the definition and format for your core data and should describe your business in some way.
These models are composed of entities – something found in the real world, such as a purchase order or service agreement. The connections between entities in a data model are called relationships. These relationships reflect business rules, or the rules you use to operate your business, such as “a salesperson can have more than one strategic account.”
Data models should in some way describe your business. They help answer questions such as:
- What is the definition of a customer? Of a prospect? A deal? Something more mundane, such as address, etc.?
- Where is the data stored?
- How is the data structured?
- Who owns the data?
- Who uses the data?
What You Need to Create Your Data Model
Bill Kent in his book, Data and Reality: A Timeless Perspective on Perceiving and Managing Information in Our Imprecise World, compares data models to road maps. However, he emphasized the differences between the real world and the world of symbols when he wrote, “Highways are not painted red, rivers don’t have county lines running down the middle, and you can’t see contour lines on a mountain.” The use of data models is the process of understanding what the data means and how the data elements relate together.
With this information, you can begin to understand what creating a data model entails: acquire the business requirements and purpose of the model; identify/create the entities, their definitions, and attributes; determine the relationship between the entities; develop your naming conventions, normalize the data; and validate the model.
As you can imagine, updating data models can be difficult and time consuming. There is also an underlying assumption that the database schema will be defined early in the model development and then left alone. In a world where the concept of agile reigns supreme, that is being nimble enough to respond quickly to changes that may happen to your customers or in your market, having data models can appear to be incongruent. However, agile has important implications …read more
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