Measuring Data Quality

💡 This is a Data Dispatch post.

I’ve had a bit of a break from Data Dispatch recently, but now I’m back with another article about data quality (DQ); or more specifically, about measuring DQ. As any data practitioner is aware, DQ is one of the most important, yet least tackled, aspect of any data pipeline.

The quality of results we deliver downstream (esp. to end users) can make/break the success of any data-driven initiative, so it’s crucial that we engage with these topics; and not just baking in some DQ checks, but also monitoring and responding to subsequent changes in quality.

The article from the Synq blog (see below) discusses measuring DQ, particularly from two viewpoints: “data asset” and “data product.” (Both are valid and useful, depending on what you want to accomplish.) It has concrete ideas around what to measure, and how to action insights.

Find the article here: https://www.synq.io/blog/measuring-data-quality.