By Steve Hoberman
Info types are the most medium used to speak facts standards from enterprise to IT, and inside IT from analysts, modelers, and designers, to database designers and builders. as a result you have to get the information version correct. yet how do you identify correct? that is the place the information version Scorecard is available in.
The info version Scorecard is an information version caliber scoring device containing ten different types aimed toward enhancing the standard of your organization's facts versions. a lot of my consulting assignments are devoted to using the information version Scorecard to my client's info types - i'll assist you to follow the Scorecard during this ebook.
This e-book, written for those who construct, use, or assessment info versions, includes the information version Scorecard template and an evidence in addition to many examples of every of the 10 Scorecard different types. There are 3 sections: In part I, facts Modeling and the necessity for Validation, obtain a brief info modeling primer in bankruptcy 1, comprehend why you will need to get the information version correct in bankruptcy 2, and find out about the knowledge version Scorecard in bankruptcy three. In part II, facts version Scorecard different types, we'll clarify all of the ten different types of the knowledge version Scorecard. There are ten chapters during this part, each one bankruptcy devoted to a particular Scorecard class:
- Chapter four: Correctness
- Chapter five: Completeness
- Chapter 6: Scheme
- Chapter 7: constitution
- Chapter eight: Abstraction
- Chapter nine: criteria
- Chapter 10: clarity
- Chapter eleven: Definitions
- Chapter 12: Consistency
- Chapter thirteen: Data
In part III, Validating information versions, we'll arrange for the version evaluation (Chapter 14), conceal find out how to support in the course of the version overview (Chapter 15), after which evaluation a knowledge version dependent upon an exact undertaking (Chapter 16).
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When I read a relationship, I start with the entity on the one side of the relationship (the parent entity) first. ” I also always use the word each in reading a relationship, starting with the parent side. The reason for the word each is that you want to specify, on average, how many instances of one entity relate to an entity instance from the other entity. There are two types of relationships, identifying and non-identifying. An identifying relationship is shown with a solid line and means that the entity on the many side (the child) is always going to be a dependent entity to the entity on the one side (the parent).
15 5 How well does the model leverage generic structures? 10 6 How well does the model follow naming standards? 5 7 How well has the model been arranged for readability? 5 8 How good are the definitions? 10 9 How consistent is the model with the enterprise? 5 10 How well does the metadata match the data? 10 TOTAL SCORE 100 Each of the ten categories has a total score that relates to the value your organization places on the question. Because we want to express the result as a percentage, the total must equal 100.