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Data quality management begins with data governance

Data quality management begins with data governance -- that means having the right strategy, people and application.

I'm beginning a data quality management initiative. What are the most important steps one needs to take in order to ensure the most flawless data quality? Also, which is more important, the application or the people?

Well, that is a short question that would require a book-length answer to do it justice. Instead of inundating...

you with information, let me give you a few high-level pieces of advice to get your data quality management initiative moving on the right track. First of all, you need to be sure that the executives at your company recognize the data quality problem and endorse the need to rectify it. By this I mean a couple of things. Data (perhaps, more accurately, information) needs to be treated as a valuable corporate asset. This means imbuing data with the same value as your other corporate assets – and then treating it accordingly. What are your other corporate assets? Capital, human resources, intellectual property, office buildings and equipment, and so on. You protect, manage, inventory and even model all of these assets (what is an org chart but a model of your human resources?). Executives do not need to be told to manage these assets, but perhaps they do when it comes to data. Have you defined and inventoried all of the critical data elements needed by your organization? Does your company know where every piece of data is? And yes, I am talking about copied data – even in Excel spreadsheets on your user's desktops.

Only when you know what it is that you are dealing with can you ever hope to ensure that it is accurate. With that in mind, how is data governance implemented (if at all) in your organization? Data governance encompasses the people, processes and procedures to create a consistent, enterprise view of a company's data in order to increase consistency and confidence in decision making, decrease the risk of regulatory fines and improve data security. Consider these questions:

  • Does your company have a team of IT professionals focused on data governance?
  • Or do you just have the DBA group, with anything even remotely relating to data getting foisted upon them?
  • Is IT aligned with business so that each data element gets the proper treatment it requires for the business as well as in terms of governmental regulations?
  • Or do you hobble along with IT and business interacting only when necessary to gather program and database specifics?

If you are hobbling, consider working to build a data governance practice before you hone down into clearing up all of your data quality problems. Look for a good consultant or two to come in and analyze your organization and give you advice on what you need to do to initiate data governance with an eye toward treating data as a corporate asset.

Of course, you can always take some baby steps along the way and do not have to implement a grand data governance practice before doing anything. Procuring and implementing a data profiling tool can help to show you the existing state of your data – and perhaps help you start cleaning up your data.

Good luck.

More information on data quality management and data governance

 

This was last published in February 2007

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