What's the point of analyzing incorrect, out-of-date or mislabeled data?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 Arkady's take on the data quality tools and technologies currently on the market (17:00).
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. Arkady is a frequent speaker at various conferences and seminars, author of the aforementioned Data Quality Assessment book, and a contributor to many journals and on-line publications.
| Download the podcast Find out how a data quality assessment can help identify, fix data quality problems | |
| For more data quality news and best practices | |
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