Data Quality Rules: Have you got started yet?
If there is one technique above all others that have helped organisations I’ve been involve with take their data quality efforts to the next level it is the establishment of a data quality rules process.
In my very first organisation, back in the early nineties, we implemented a simple data quality rules policy that ensured that all data coming into the organisation was documented, validated, monitored and governed. The results were phenomenal. Our lead times tumbled and productivity went through the roof.
The reality is that all organisations possess data quality rules but they’re typically scattered widely (and wildly) 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.
I hope you find this virtual book of resources useful and feel free to post your recommendations and tips in the comments below.
Chapter 1: Setting the Scene for Data Quality Rules
- Data Quality and Business Rules Explained, featuring Ron Ross
- Creating Effective Business Rules, featuring Graham Witt
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 Firewall and SLA
- 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
- Data Quality Assessment by Arkady Maydanchik
- Enterprise Knowledge Management: The Data Quality Approach by David Loshin
- The Practitioner’s Guide to Data Quality Management by David Loshin
- Data Quality: The Accuracy Dimension by Jack E.Olson
- Practical Data Migration by John Morris [Explains how to set up a Data Quality Rules Process throughout a Data Migration Project]
Image credits: cc Flickr Joe Shlabotnik