Entries Tagged 'Data Modeling' ↓

An important piece of Data Governance is enforcing the policy and governance over data that the council has put in place. This can be one of the most challenging pieces of data governance, and it really occurs at the point where a data governance program and data quality program intersect. The position you don’t want to find yourself in is only being able to find data violations after they occur, through some kind of profiling tool.  While this is certainly a reactive piece you need, you also need to have proactive data governance practices that will find data changes and missuse before it occurs.

Think you’d have to be Nostradamus to do that? Keep reading for 3 ways to be proactive in enfocing data governance policies.
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I got an email after my post on Tuesday about working with your Data Modelers. It was from a guy who works at a mid-size company that runs pretty lean, meaning he doesn’t have much support from the IT staff because they are busy on other projects. He said he didn’t have data modeling tools at his disposal, so how can he track his Data Governance Program for the long-term?

I thought about this for a while. I’m so used to a large corporation where there are lots of tools and resources available (although they aren’t waiting for you to ask them to do something) so I had to think about this one for a bit…. What would I do if I was in his situation?
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If Data Governance is your program/project to manage, think of the Data Modeling Team and their tools as your foundation. A good Data Governance Program needs to be built atop a top-notch Data Model. Sure, you can have Data Governance without a good data model, it’ll just be a lot harder and a lot more time consuming. See this post on data governance failures for a recent study stating a high percentage of Data Governance programs fail - and my thoughts on that.
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