This article is more of an informed opinion rather than just a description of the lay of the land for Data Governance. Prodago has been thinking about this a lot. In part, we are selfishly trying to clarify our messages and boil down the problems affecting organizations to their essential, painful components. But in part, we are also exposing what we all know to be true: Data Governance exists in most organizations, but it fails to live up to the value executives expect.
It helps to identify the problems and their root causes. This is the first step in finding a long-lasting solution.
The article means to stir the conversation for senior leaders to understand better where things break down and examine how we can address them.
How did we get here?
Traditional Data Governance was designed years ago, at a time when IT needed to involve the business in making decisions around data. It started with system access, data quality, and data definitions. Since then, it has evolved to manage quite a few more things (see 9 data aspects managed by successful Information Governance programs).
But quite a few pressures are forcing us to reconsider HOW we are to govern data. What makes it particularly difficult for leaders is that we are used to observing a problem and then solving it. But more problems to solve have been slowly creeping upon us. We just didn't see them coming!
If we step back a little, the combination of these trends together has created the perfect storm:
We are managing and generating more and more data.
The cloud has infinite performance, but it takes time to move everything there. So we find that there are more and more environments where data sits or holding copies of it.
AI, analytics, and automation mean we need to use this data in more use cases.
Perhaps related to the proliferation of use cases, but for sure, no one will argue that more people need the data to do their work.