Consistency in Data Management: how about Data Governance?

Written by Ronald Baan

Ronald is a data enthusiast who spends his time sharing his passion in data with others.

9 January 2023

When it comes to data management, there is a lot of talk about data governance and data quality. Very important topics that definitely need attention.

Focusing on that alone is not enough. Getting data management to a sufficient level to support organisational goals will only succeed if there is a consistency and balance between all components of data management.

The parts of data management you want consistency on are no different than the consistency you want on other important processes.

Only when data governance is set up based on the data strategy, only when people and organization, data-driven processes, data capabilities and data are aligned, will you achieve your goals.

If you focus primarily on data governance and “forget” or give too little attention to the other components, you will end up with a very buttoned-up, risk-averse and rigid environment that will not help support organizational goals.

Dependance and Interaction


  • People and organisation: ensure that data governance is embedded in the organisation, with appropriate advisory bodies, data expertise throughout the organisation (both through the functional organisation with data officers, data managers, data stewards, etc., and through sufficient data knowledge at all levels of the organisation, including (senior) management);
  • Data-driven Processes: ensure that processes actually work better and more efficiently based on data and also set up processes to better manage data, i.e. processes for data;
  • Datacapabilities: Some of these will already be extensively available, others less so. There is a tendency, because data capabilities certainly also have a large IT component, that systems are purchased for these, such as a data catalog, data quality monitoring, ETL tools, etc. Precisely the consistency and balance for what the business needs deserves attention here;
  • Data: make sure data is suitable for multiple uses, think quality and privacy, but also meaning and coherence.

With data governance you try to get these things done, but the above conditions must also be met, otherwise data governance is just a paper world.

You may also like…

Change, Stability and Dynamics

Change, Stability and Dynamics

The next time your boss (or whoever) talks again about that data management should be at a higher maturity level (or...