Completeness, Consistency, and Integrity of the Data Model
Purpose
This appendix discusses how to assess the completeness, consistency, and integrity of the data model and metadata associated with the data model as part of data quality assessment for a database (as described in DQAF Measurement Types 1–5) (See Table C.1.). To be meaningful, data requires context. In databases, the data model, including its metadata, contributes significantly to this context. If information in the model is incomplete or inconsistent, it introduces risk. Data consumers may make poor decisions about which data to use, and technical processes may not function as expected.
Table C.1
Measurement Types Related to the Completeness, Consistency, Integrity of ...
Get Measuring Data Quality for Ongoing Improvement now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
