By Steve Hoberman
Information 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. for that reason you have to get the knowledge version correct. yet how do you establish correct? that is the place the information version Scorecard is available in.
The info version Scorecard is a knowledge version caliber scoring device containing ten different types aimed toward bettering the standard of your organization's facts types. a lot of my consulting assignments are devoted to making use of the information version Scorecard to my client's info types - i'm going to assist you to observe the Scorecard during this publication.
This publication, written for those who construct, use, or evaluate info types, includes the information version Scorecard template and an evidence besides many examples of every of the 10 Scorecard different types. There are 3 sections: In part I, information Modeling and the necessity for Validation, obtain a brief info modeling primer in bankruptcy 1, comprehend why you will need to get the knowledge version correct in bankruptcy 2, and find out about the information version Scorecard in bankruptcy three. In part II, info version Scorecard different types, we are going to clarify all of the ten different types of the knowledge version Scorecard. There are ten chapters during this part, every one bankruptcy devoted to a particular Scorecard classification:
- 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 info versions, we are going to organize for the version evaluation (Chapter 14), disguise the right way to support through the version assessment (Chapter 15), after which assessment an information version dependent upon a precise venture (Chapter 16).
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Extra resources for Data Model Scorecard: Applying the Industry Standard on Data Model Quality
The entity Account can have instances of Bob’s checking account, Bob’s savings account, Joe’s brokerage account, and so on. Entities may be described at conceptual, logical, and physical levels of detail. The conceptual means the high level business solution to a business process or application effort frequently defining scope and important terminology, the logical means the detailed business solution to a business process or application effort, and the physical means the detailed technical solution to an application effort.
Surrogate Key A surrogate key is a unique identifier for a table, often a counter, usually fixed-size, and always system-generated without intelligence, so a surrogate key carries no business meaning. ) Surrogate keys should not be visible to the business but should remain behind the scenes to allow for more efficient navigation across structures and to facilitate integration across applications. Surrogate keys are also efficient. You’ve seen that a primary key may be composed of one or more attributes of the entity.
Surrogate keys are useful for integration, which is an effort to create a single, consistent version of the data. Applications such as data warehouses often house data from more than one application or system. Surrogate keys enable us to record correlations between information about the same entity instance that is identified differently in each source system when those correlations were not obvious from common identifiers. When using a surrogate key, always make an effort to determine the natural key, which is what the business would consider to be the way to uniquely identify the entity, and then define this natural key as an alternate key.
Data Model Scorecard: Applying the Industry Standard on Data Model Quality by Steve Hoberman