Producing Adequate Definitions

Producing Adequate Definitions

We know how important definitions are, yet we also know that definitions are often missing or of poor quality in data deliverables. Over the years I have used a number of techniques to ensure adequate definitions are present. For example, one technique is to write the attribute definition before naming the attribute. This not only guarantees you’ll have a definition, but you will also often come up with a better attribute name. What techniques do you use to produce adequate entity and attribute definitions?

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2 Comments

  1. Becky Schmidt 4 years ago

    Hi Steve! I’m wondering, in terms of definitions, what is the difference between an attribute and a measure? Thanks! Becky

    • Author
      Steve Hoberman 4 years ago

      Hi Becky, an attribute is a property that can describe, identify, or measure an entity, so a subset of attributes will be measures. For example, Customer Number may identify a Customer, Customer Last Name may describe the Customer, and Customer Purchase Quantity may measure something about that customer. This last attribute is an example of a measure, a property that can be viewed at various levels of granularity such as by date and month. In the context of dimensional modeling, a measure takes on a more precise definition – not only is it an attribute that can be viewed at various levels of granularity, but a measure is also an indicator as to how well a business process is doing. For example, Customer Purchase Quantity might be an indicator how well the sales business process is doing.

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