Recently in Data Quality Category

Just published! My new book on data quality improvement, called The Practitioner's Guide to Data Quality Improvement was released a few weeks ago and is now available. The book provides practical information about the business impacts of poor data quality and provides pragmatic suggestions on building your data quality roadmap, assessing data quality, and adapting data quality tools and technology to improve profitability, reduce organizational risk, increase productivity, and enhance overall trust in enterprise data.

I have an accompanying web site for the book at www.dataqualitybook.com. At that site I am posting my ongoing thoughts about data quality (and other topics!) and you can download a free sample chapter on data quality maturity!

Please visit the site, check out the chapter, and let me know your thoughts by email: loshin@knowledge-integrity.com.

I will be the guest speaker at an executive breakfast seminar in Boston on October 28^th to discuss the critical link between Data Quality, MDM and Data Governance. If you are interested in attending, please register through http://bit.ly/cM5q7k - looking forward to seeing you there!

Last week I had an interesting discussion regarding technical aspects of data cleansing, particularly in the context of acquired data. The challenge posed was that the organization needed to collect data sets from numerous sources with no ability to introduce any types of data controls or dat avalidations. In other words, the data they got was what it was, and if they wanted to use it, they'd have to clean it up themselves.

So the discussion led to talk about tools for cleansing, and I mentioned that most products today provide some means of parsing and standardization as  aprelude to entity resolution, matching, and consolidation. In fact, I will be continuing this discussion at a web seminar next week on Parsing and Standardization, and I hope you can attend!

As more organizations are starting in earnest to consider deploying master data systems, they are also beginning to see where some fundamental issues may block the creation of a full-scale master data repository. This had me thinking about potential ways around some of these issues (especially where governmental regulations prevent moving data across borders!), and one aspect I started considering is the use of a data federation or virtualization model that can abstract the pereption of a unified view without necessarily copying the data.

At the same time, I was approached by Composite Software to do some research on the fesibility of incorporating data quality management techniques within a data virtualization framework. That activity only has continued to pique my interest in integrating virtualization and MDM, and it also allowed me to explore some ideas I explored in my book on data quality management. Meanwhile, the result of that task is an interesting white paper, which you can access via Composite's web site - search down to the "analyst reports" section of the page. Let me know your thoughts!

In my most recent article on b-eye-network, I discussed the questions raised as a result of serious consideration of instituting MDM, and how that directly depends on sound data management practices associated with data quality and more importantly, data governance. If this interests you, I will be participating in a set of executive lunch meetings with Initiate Systems to discuss these ideas in greater detail, one in Chicago on May 25 and one in San Jose on May 26. Here are the links for more information:

Chicago, May 25 at 10:00 AM - 1:00PM CDT

San Jose, May 26 at noon - 3:00PM PDT

If you plan to go, let me know!