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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!

In the past week, we have had a number of conversations with folks struggling with specific aspects of data integration for master data management. The main issue is that secondary users of what will eventually be master data do not always necessarily bound to abide by the primary users' data definitions. For example, the concept of "customer" means something different to the sales department than it does to those in customer support.

The upshot is that as data element definitions are reinterpreted, the results of sums, counts, and other aggregations start to be skewed. Ultimately, resulting reports are inconsistent, leading to a need for reconcilations, then loss of trust in the master data asset.

One way to address this is a concerted effort to normalize semantics prior to executing the data consolidation. This may shake out semantic inconsistencies and reduce the need for reconciliations.

More importantly, it implies the need for best practices in developing master data models. To that end, I will be presenting a talk on Accelerating MDM Initiatives with Master Data Modeling at a webinar sponsored by Embarcadero on July 28th. Lots of folks have already signed up, and I hope that it will provide an open forum for discussing some critical issues regarding master data modeling.

Posted July 21, 2010 4:52 PM
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