Podcast

Data quality assessment helps identify, fix data quality problems


Don't miss the other installments in this data quality management guide
Managing data quality programs during a recession
Trends in the data quality market
Avoiding data quality pitfalls and using data quality tools for discovering new opportunities
Q/A: Identifying data quality problems with a data quality assessment
FAQ: Best practices/tips for data quality


What's the point of analyzing incorrect, out-of-date or mislabeled data? Actually, that's a trick question. There really is no point, which is why achieving comprehensive data quality management – that is, ensuring the accuracy, reliability and effectiveness of data – and overcoming data quality problems is so critical to business success.

But data quality is still an emerging field, one often overlooked by companies and organizations. To help understand how to start a data quality program, SearchDataManagement.com caught up with Arkady Maydanchik, a member of the Data Quality Group and author of the recent book Data Quality Assessment.

In this 20-minute podcast, appropriate for both business and IT professionals, listeners will:

  • Find out how to get a handle on your data quality needs through a data quality assessment (1:28).
  • Learn why data quality rules are crucial to the outcome of any data quality project (4:11).
  • Learn how to ensure your data quality assessment is comprehensive and complete (7:12).
  • Get a lesson on data quality scorecards and how to design and use them (9:54).
  • Find out how to improve metadata quality with a data quality metadata warehouse (13:37).
  • Get Maydanchik's take on the data quality tools and technologies currently on the market (17:00).
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Data quality starts with a data quality assessment

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About the speaker: Arkady Maydanchik is a recognized practitioner, author and educator in the field of data quality and information integration. His data quality management methodology was used to provide data quality services to numerous Fortune 500 companies. Maydanchik is a frequent speaker at various conferences and seminars, author of the book Data Quality Assessment and a contributor to many journals and online publications.


For more data quality news and best practices:

Learn how integration competency centers centralize data integration projects and help improve data quality.

Find out why Informatica bought identity resolution software maker Identity Systems.

Get a definition of high-quality information, and find out what it means for overall data quality.

Find out where to go to get unbiased assessment and analysis of data quality management tools.

Learn the fundamentals of getting started with a data quality program, from understanding business drivers to evaluating data quality software options.

Email SearchDataManagement.com with story ideas or comments about data quality.


Don't miss the other installments in this data quality management guide
Managing data quality programs during a recession
Trends in the data quality market
Avoiding data quality pitfalls and using data quality tools for discovering new opportunities
Q/A: Identifying data quality problems with a data quality assessment
FAQ: Best practices/tips for data quality


 


This was first published in May 2008

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