Data governance
Data governance establishes responsibilities and criteria for managing information as an organisational resource
What it means, how it is used and where it comes up, with its related concepts.
What it is and how it works
It includes definitions, access, quality, traceability and retention. Its application should support specific uses and resolve conflicts. Drawing up policies without owners or operational processes does not guarantee that data is reliable or usable.
Topics
Frequently asked questions about Data governance
Is data governance only the responsibility of the IT team?
No. IT can implement controls and tools, but the areas that produce and use the information must agree on what it means, what quality it needs and who is accountable for it. Identify a responsible party with decision-making authority for each relevant domain. If business definitions remain in conflict, a catalog tool can document the disagreement, but it cannot resolve it on its own.
Where do you start with data governance without trying to govern all of an organization's data?
Start with a specific use case and the data that is critical to it. You can agree on its definitions, owners, quality controls and how issues will be resolved. The scope should make it possible to check whether the information is fit for the intended decision. Documenting everything before solving a real problem can consume effort without improving how the data is used.
Is cleaning a database the same as implementing data governance?
No. Cleaning fixes specific problems, such as duplicates or inconsistent values; governance establishes how decisions are made to prevent, detect and resolve them throughout the lifecycle. Investigate where they originate and what responsibility is missing. If the process that generates the error stays the same, a freshly cleaned database can deteriorate again. Quality should be assessed against the intended use.