Run a successful Data Governance Program

Here is the latest news in the Data Governance Industry


New Study Shows That Most Firms Struggle with Data Integrity Issues - This article states “most firms struggle with Data Integrity Issues” and lists Data Governance as part of the solution to this problem.

Business Intelligence in Healthcare: The Drivers - Consultant Jill Dyche muses about Health Care issues, and new attempts to fix their old problems.

TIBCO’s New Master Data Management Software Offers Industry-First Feature Set - Tibco has released new Master Data Management Software

Is Informatica An Acquisition Target? - It won’t help you with your program, but if you’re interested in the industry or if you use Informatica, this is an interesting article about how Sramana Mitra thinks Informatica is an acquisition target

Q&A: The Ins and Outs of Enterprise Master Data Management - A good article on the future of MDM

Varonis Joins Data Governance Council Formed by IBM — Some info on Varonis and the IBM Data Governance Council

Wednesday at the conference began the series of shorter sessions. The day kicked-off with the one-hour keynote from Elizabeth Kirscher, President of Morningstar’s Data Services Business. Her presentation, titled “When Data Quality Drives Revenue“, centered around the accomplishments of Morningstar in the data management field and the road that they took to get there. Elizabeth’s background was in sales, so when she began leading the Data Services Business she didn’t quite have the technical background that one would associate with that position. This just goes to show that many data issues reside on the business side, not in IT. In her tenure at Morningstar, where her team is seen as a profit center (lucky her!), she has gone through many regulation and standardizations as well as mergers and acquisitions. Listening to her stories about these business moves was very interesting.
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I attended an all day session by Danette McGilvray titled “Ten Steps to Quality Data and Trusted Information” at the IAIDQ Conference. The session provided a really nice framework that you can follow, step-by-step, to implement a strong Data Quality Program in your organization. Danette is the President and Principal of Granite Falls Consulting, Inc. a firm “specializing in data quality management to support key business processes around customer satisfaction, decision support, supply chain management, and operational excellence.” Throughout the presentation it became very obvious that Danette has “been there and done that” many times over. Her examples of successes and failures on projects she has worked on throughout her career really helped crystallize why her ten steps are effective.
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On the first day at the Information and Data Quality Conference, I attended the session, “Using Data Profiling for Proactive Data Quality Improvement“. That session was for the first half of the day, so for the second half I attended the Len Silverston session titled “Power and Politics in Data Quality Improvement Efforts“. This was a great session that had very little to do with data theory and data management, and a lot to do with interoffice dynamics. The session opened up with the question, “What is the biggest problem in data quality today?” Many good answers were tossed out by the attendees, but I think the answer that Len submitted trumped them all… read on for the answer.
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If you have been following the open source movement (wikipedia page), you’re probably very excited about the products that are coming out of it. In short, open source means that the product is free, peer-edited, and often times better than its cost-based counterparts. Take Firefox for example; Firefox is a web browser that runs faster than Internet Explorer, has a far superior security system (fewer exploits and viruses) than Internet Explorer, and this was all created by a not-for-profit foundation called Mozilla with the help of thousands of volunteers. You can click here to install .
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This past week I attended the Information and Data Quality Conference at the Palms Hotel in Las Vegas. The conference material was great, and because data quality is an emerging discipline just as data governance is, there were many different approaches and methodologies to implementing data excellence in your organization. Last week I opened up the opportunity for you to steer my data quality conference experience by allowing you to email me with sessions that you’d like notes from… One person took me up on the offer and later this week I’ll provide you with my notes from the session he requested, “Managing Data Quality in an ERP Environment” by Danette McGilvray.

I’d like to start, though, with key takeaways from my half-day session (on the 1st day): “Using Data Profiling for Proactive Data Quality Improvement” by David Plotkin of Wells Fargo Bank. As you probably know by now, I maintain that a good data quality program is a key piece to making Data Governance successful (and vice-versa). This session included some great tips for starting and sustaining data quality. Read on for notes from the session…
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One document that is an absolute must-have for your program is the “Data Governance Policy Document”. This is a document that states what the Data Governance Office (and council) will not allow. It can also state what you do allow, but I’ve found its easier to just list what is now prohibited. Why is this document so valuable? Because there will absolutely be times when someone wants to do something that the DGO is staunchly against, and having a formal policy in place gives you something to reference rather than just “because I said so”. Putting this document together is fairly easy, below are some tips to get you started.
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Here are a few articles to expand your data horizon…

Governance Portal
This is a pretty good article in DMReview about the beginning stages of data governance. It states that, “data quality is the first step towards a proactive data governance initiative”. Its a very timely post, as I’m headed to the Information and Data Quality conference next week, and it gives a nice perspective to judge the various venders that will certainly be presenting their wares.

What’s exciting about LogLogic?
This short article from Philip Howard reviews LogLogic, a product that enables you to bring all of your log data into a single place for analysis. Phillip acknowledges that logs are a snoozefest, but what LogLogic does certainly seems valuable. He touches on data governance at the end, mentioning that the output of LogLogic analysis will help in the data governance program.

The Impact of Data Governance on M&A
Phillip really cranked out the articles for IT-Director this week… In this writeup he makes the case that if a company wants to be acquired, “then it would be a good idea to have good data governance in place.” Likewise, if you are looking to aqcuire companies, it would be very wise of you to look for companies that have good data governance in place. This is really an interesting read…

This weekend I’m headed out to the Information & Data Quality Conference in Las Vegas. I’m really excited about the conference because the agenda looks awesome (not to mention they also picked a great locale). For all of you unable to attend, you can view the agenda here; this is what I’m going to do… If you have a particular interest in any of the sessions, email it to me, and I’ll attend it and then give you my notes and thoughts on it. In addition, I’ll be blogging throughout the conference about the various events.

If you haven’t yet subscribed to this blog, take a second and do so by entering your email address in the box below. I’m going to pick up some goodies at the conference and give them away to email subscribers! If you’ve already subscribed you’ll automatically be entered.

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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