Data quality metrics

There is a pandemic happening in the enterprise. Companies are unaware of the quality of data they are dealing with. Fixing Data Quality starts with understanding what the damage is first. So, for those that are fixing data quality without knowing what benchmarks are in place, you are essentially beating a dead horse. At CluedIn, Data Quality metrics is one of the first experiences that our customers experience. It is actually one of the more exciting parts of using CluedIn, that moment where you integrate data and the system tells you what quality you are dealing with. In fact, you receive 19 different metrics of Data Quality. The intention of this white paper is for our customers to understand what these different metrics are tracking.

Without a doubt, when our customers see their data quality scores, the first question they typically will ask is “What dictates accuracy?”. The first answer will always be that, “Accuracy” is open to interpretation, and what you get with our quality scoring is our interpretation of it. Of course, we allow our customers to change or extend this, but at heart, working with the customers that we have, we believe we have a good default implementation.

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