Data Governance is not about more data.
It is about more trust.

The real problem with unclear data ownership usually does not appear when everything is working normally. It becomes visible the moment something goes wrong. A report shows incorrect numbers. A KPI suddenly changes. Different teams have different results for the same metric. And then the most common process inside many organizations begins: finding someone to blame. One team says the issue comes from the source system. Another says the methodology is wrong. Someone else claim

At one point, I was trying to identify the owner of a specific data set inside a company. The question sounded simple: “Who is responsible for entering this data?” But the answers were surprisingly unclear. “Maybe this department.” “I think that team handles it.” “I’m not really sure who owns it now.” Eventually, we discovered that data related to store surface areas — something that would logically belong to Operations — was actually being maintained by a completely differen

One of the biggest misconceptions about Data Governance is the idea that: “more controls automatically mean better data.” In reality, too many controls can become a serious problem. Especially when validation rules generate large numbers of false positives. At first, users pay attention to alerts and warnings. But when the system constantly reports issues that are not actually real problems, something dangerous starts happening. People slowly stop trusting the controls themse