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David Loshin

Welcome to my BeyeNETWORK Blog. This is going to be the place for us to exchange thoughts, ideas and opinions on all aspects of the information quality and data integration world. I intend this to be a forum for discussing changes in the industry, as well as how external forces influence the way we treat our information asset. The value of the blog will be greatly enhanced by your participation! I intend to introduce controversial topics here, and I fully expect that reader input will "spice it up." Here we will share ideas, vendor and client updates, problems, questions and, most importantly, your reactions. So keep coming back each week to see what is new on our Blog!

About the author >

David is the President of Knowledge Integrity, Inc., a consulting and development company focusing on customized information management solutions including information quality solutions consulting, information quality training and business rules solutions. Loshin is the author of The Practitioner's Guide to Data Quality Improvement, Master Data Management, Enterprise Knowledge Management: The Data Quality Approachand Business Intelligence: The Savvy Manager's Guide. He is a frequent speaker on maximizing the value of information. David can be reached at loshin@knowledge-integrity.com or at (301) 754-6350.

Editor's Note: More articles and resources are available in David's BeyeNETWORK Expert Channel. Be sure to visit today!

March 2010 Archives

On Monday, march 15 I conducted a full-day master data management tutorial at the Enterprise Data World conference. As a forum for discussing pragmatic MDM best practices, one section of the day was set aside for a panel discussion among representatvis from four vendor products:

  • Dan Soceanu from DataFlux
  • Marty Moseley from Initiate Systems - An IBM Company
  • Ravi Shankar from Informatica (formerly Siperian)
  • Jim Walker from Talend

I posed the question to all four: What defines data as "master data"? The first round of answers focused on the standard answer: data concepts that "are important" to the business and are shared by two or more applications. My reaction to this response was that it was not a practical guide, and then rephrased the question: What can the people in the audience do when they got back from the conference to start identifying data entities as master data?

Again, I did not get the answers I was looking for - all four suggested that the task was not one that could be done at your desk, that it required knowledge of the business, that subject matter experts had to be consulted.

All true, but again, not executable, so I reframde the question again: knowing that there was bound to be variation, replication, duplication, redundancy, differences in semantics, what is a process for reviewing the data to decide which data element of which data entities belongs in a unified master view.

At that point the answer became a little clearer: you can't tell unless you understand what each data element is, how it is used, what its definition was, how many application sused, in what type of usage scenarios. In addition, you needed oversight of the process for analyzing the data and capturing the results, sharing, and having all that information validated by subject matter experts.

As moderator, I responded by summarizing: "in order to determine what data is master data, you need to analyze the data, document all the information about the data, and have policies for overseeing that process. That sounds like data profiling, metadata management, and data governance." (nods all around)

But is has to be more than that; there has to be a more operationalized method that results in a clear determination of which data elements of which data entities are to be mastered.

Posted March 17, 2010 1:01 PM
Permalink | 3 Comments |


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