Business Intelligence Network - The Vision for BI and Beyond

In this 20-minute podcast, appropriate for both business and IT professionals, listeners will find out how to get a handle on data quality needs through a data quality assessment, learn why data quality rules are crucial to the outcome of any data quality project, learn how to ensure your data quality assessment is comprehensive and complete, get a lesson on data quality scorecards and how to design and use them, find out how to improve metadata quality with a data quality metadata warehouse, and get Maydanchik's take on the data quality tools and technologies currently on the market.

What's the point of analyzing incorrect, out-of-date or mislabeled data?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).
• And get Maydanchik's take on the data quality tools and technologies currently on the market (17:00).