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  • Ambiguity in Definitions

    I review many data models throughout the year using the Data Model Scorecard technique, and over 95% of the entity and attribute definitions reviewed lack precision. There are certain terms in a definition that, if not explained, automatically make the definition imprecise and vague. The terms...

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    Steve Hoberman's first word was "Data"
  • Is stability an important property for a candidate key on the logical data model?

    A candidate key is an attribute (or set of attributes) that identifies an entity. A candidate key is either a primary key or an alternate key. So for example, in the following Student entity, there are two candidate keys: a primary key on Student Number and...

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    Steve Hoberman's first word was "Data"
  • Learning more about JSON

    One of my New Year’s Resolutions this year is to learn more about JSON. More specifically, how does JSON act and what are all of the JSON structures, such as nested arrays, which differ from those in our relational world? (I am also currently looking for...

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    Steve Hoberman's first word was "Data"
  • The fifth of the five killer questions: Omissions

    In the free Data Model Scorecard Validation Tool, there are five “killer” questions out of the over 150 questions that are part of the tool, that if answered improperly will automatically score the model with the lowest setting of “Poor”. If you’ve used the tool, you...

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    Steve Hoberman's first word was "Data"
  • The fourth of the five killer questions: Time

    In the free Data Model Scorecard Validation Tool, there are five “killer” questions out of the over 150 questions that are part of the tool, that if answered improperly will automatically score the model with the lowest setting of “Poor”. If you’ve used the tool, you...

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    4
    Steve Hoberman's first word was "Data"