On linkedin from "The Cyber Security Hub" shared a nice booklet about data governance:
An like always: It is only a booklet with about 25 pages - so this is not really a deep dive into this topic, but it gives you a good overview and of course a good motivation:
These include the need to governdata to maintain its quality as well as the need to protect it. This entails the prerequisite need to discover data in your organization with cataloguing, scanning, and classifying your data to support this protection.
and if this is to abstract, you should consider the following use case (and i think this use case has to be considered):
However, for AI to become effective, the data it is using must be trusted. Otherwise decision accuracy may be compromised, decisions may be delayed, or actions missed which impacts on the bottom line. Companies do not want ‘garbage in, garbage out’.
The booklet contains the sections "Requirements for governing data in a modern enterprise", "components needed for data governance", "technology needed for end-to-end data governance" and "managing master data". All sections do not provide a walk through for achieving a good data governance, but there are many questions listed, which you should answer for your company and then move forward.
If you already have a data governance in place: This book is a good challenge for your solution. And for sure you will find some points, which are missing :)
