In today's fast-paced world, everyone is under constant pressure to produce at a rapid pace. When we eat at a restaurant, we expect to be served quickly; when we are shopping, we don't like waiting in line. Similarly, our business users expect the business intelligence team to deliver requested capability quickly, and anything that is perceived as delaying the result is not well received. Data modeling is one development step that does not directly generate code, and, adding insult to injury, we try to insist that the business user participates in the modeling effort. In this setting, it's not surprising that we're often asked to skip developing a business data model. It leaves us with two challenges: explaining why this data model is important and finding a way to develop the model as quickly as possible.

A business data model (a.k.a., conceptual model or enterprise model) is a representation of the information used in an enterprise from a business perspective. The model encompasses the business rules about the information and is independent of organizational, procedural and technical constraints. At any point in time, there is only one business data model in an enterprise. This model is portrayed in an entity relationship diagram and is represented in (at least) third normal form. In that form, there is no data redundancy, and business rules are enforced through relationships and referential integrity. Four areas in which the business data model helps are: designing the physical databases, describing project scope, guiding data profiling efforts and supporting transformation mapping.  

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