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