Data Governance Issues{2}

by Chris S
This article brings to light the importance of data governance. Basically data governance is the discipline of converging data quality, management, policies and risk management revolving around the handling of data. Summed up, its just like talking about data integrity. There are five steps toward data governance, starting with a working group, developing an operational framework, choosing a pilot initiative, monitor and learn, and refine and grow. While collecting data in the database  is extremely important for running a business, one may overlook how the data is governed. Apparently data governance is recognized as an important need for businesses, but it is not always taken care of properly. When it comes time to extract certain data for reporting or analyzing purposes, there can and often are complications.

In the example given in the article, it shows a customer table much like the one from our class. The first name of the customers is only partial, like there is a Jane in the first spot, then initials JD in another spot. Or like the section for the state is Kentucky and KY. These are very simple issues and there are definitely much more important issues that can arise from improper data governance with a business. There were also issues given with nulls, like instead of properly getting accurate information, “something” is just inserted into the system so whoever is working on it can just move on quickly to the next thing. Again these types of things can cause inaccurate reports, can be analyzed the wrong way, and ultimately lead to future wrong decisions for a business.

I believe this type of thing fits right in with what we were discussing in class, especially for part of the second project. The normalization of the data is very important. Breaking it down into universally understood meanings will prove to be much more beneficial down the road, (from the example for instance, making all the states abbreviated). This will save time and space and will still be known universally. A necessary step toward data governance can be achieved just by normalizing.


Bond, Keesa. “The Silent Problem of Data.” Database Journal, 25 Apr. 2012. Web. 28 Apr. 2012. <>.