Monday, July 6, 2009

June’s "El Festival del IDQ Bloggers”


A Blog Carnival for Information/Data Quality Bloggers

June of 2009 is gone, so it’s time to look back at the month and recognized some of the very best data quality blog entries. Like other blog carnivals, this one is a collection of posts from different blogs on a specific theme.

If you’re a blogger and you missed out on this month’s data quality carnival, don’t worry. You can always submit your brilliant entries next month. So, here they are, in no particular order.


  • Newcomer Jeremy Benson has a unique perspective of being an actuary – someone who deals with the financial impact of risk and uncertainty to a business. We know that improving data quality will certainly produce more accurate assessments when it comes to crunching numbers and calculating risk. This month’s blog entry describes how data quality is important to predictive modeling. More actuaries should understand the importance of data quality, so this is a positive step.

  • Irish information quality expert Daragh O Brien was talking about his marriage problems this month – well, at least the data quality problems with his recording of his marriage. In this post he discusses a recent experience and how it made him think yet again about the influence of organizational culture and leadership attributes on information quality success and change management.


  • Western Australian blogger Vince McBurney contributes his excellent analysis of the new Gartner Magic Quadrant for data quality tools. Vince’s analysis of the LAST Magic Quadrant (two years ago) was perhaps my biggest inspiration for getting involved in blogging, so it makes me happy to include his blog. “Tooling Around on the IBM InfoSphere” is focused on data integration topics from the perspective of an expert in the IBM suite of software tools.

  • Jim Harris takes us into “The Data-Information Continuum” to remind us that data quality is usually both objective and subjective, making reaching the “single version of truth” more mystical. The post made it clear to me that our description of the data quality problem is evolving, and the language we must use to promote our successes must evolve, too.


  • Dalton Cervo is the Customer Data Quality Lead at Sun Microsystems and a member of the Customer Data Governance team at Sun. Dalton takes us on a journey of depuplicating a customer database using a popular data quality tool. It’s great to see the detail of project like this so that we can better understand the challenges and benefits of using data quality tools.


Thanks to all the outstanding data quality bloggers this month!

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