From the course: Data Quality: Core Concepts
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Measuring data quality
From the course: Data Quality: Core Concepts
Measuring data quality
- [Instructor] So we're aware of the data lifecycle, we're aware of the stakeholders, we're aware of how data quality pops up into them, and what the signals of data quality issues look like. Now, how do you measure them? I want to bring back the DAMA data quality dimensions that we covered in an earlier chapter. These dimensions are critical for measuring data quality. Now remember, there's different dimensions or formats you can use. Whichever one your company decides on, just stick to the framework that you have. How to measure them is that you identify your most important data that needs data quality, you map the data quality dimensions to the data assets. You create aggregate metrics to represent what proportion of the data values are impacted by data quality issues, specifically among those dimensions. And then you create pass/fail logic based on acceptable values of the metric. And so as a mock example, remember our e-commerce exercise, well, that data leader got funding and…
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