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IDQ Webinars: with Dave Becker from The MITRE Corporation


Topic:

Flexible & Generic DQ Metrics, Measurements & Assessments

Abstract:

In order to improve the quality of your data it is important to first establish a baseline measurement of exactly what the quality is, and whether that level of quality is adequate for your purposes. As you proceed with your data quality improvements, you can then compare interim measured levels of quality achieved against the baseline to determine if you are making progress toward your improvement objectives. This briefing discusses a flexible and generic approach to construct DQ metrics and target thresholds, and then use them in the measurement and assessment of the quality levels of DQ improvement efforts. The approach utilizes techniques that build on the identification of DQ subjects and business rule violations. For a given data quality (DQ) subject, there are many dimensions that are appropriate to consider. Each dimension must have a separate metric. There are also multiple potential users to consider, and each usage context may require individual quality thresholds of usefulness.

Webinar report:

Recording:

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