Data Quality Rules: The Definitive Guide to Getting Started
The establishment of a data quality rules process is one technique above all will help you take your data quality efforts to the next level.
The reality is that all organisations possess data quality rules but they’re typically scattered widely across the organisation with no thought to standardisation, governance and re-use.
The following resources will help your organisation buck that trend and get into some solid data quality rules management habits and best-practices.
Chapter 1: Setting the Scene for Data Quality Rules
Chapter 2: Common Data Quality Rules
Data Quality Rules – Attribute Domain Constraints, featuring Arkady Maydanchik
Data Quality Rules – Relational Integrity Constraints, featuring Arkady Maydanchik
Data Quality Rules – Event Histories, featuring Arkady Maydanchik
Data Quality Rules – Historical Rules, featuring Arkady Maydanchik
Data Quality Rules – State-Dependent Objects, featuring Arkady Maydanchik
Data Quality Rules – General Attribute Dependencies, featuring Arkady Maydanchik
Chapter 3: Data Quality Rules in Context
How to Create a Data Quality Rules Process for Data Migration, featuring John Morris
Measuring Data Quality for Ongoing Improvement, featuring Laura Sebastian-Coleman
Chapter 4: Useful Books for Learning and Applying Data Quality Rules
Enterprise Knowledge Management: The Data Quality Approach by David Loshin
The Practitioner’s Guide to Data Quality Management by David Loshin
Practical Data Migration by John Morris [Explains how to set up a Data Quality Rules Process throughout a Data Migration Project]