What is Data Quality?

Why is Data Quality important?

Without quality data, there’s no way of ensuring that the recommended insights are accurate and will ultimately help instead of hurting your business. The more high-quality data you have, the more confidence you can have in your decisions and produce better outputs. Good data decreases risk and can result inconsistent improvements in results. Gartner and IMB estimate that in the U.S.alone, over 3 trillion dollars are wasted on poor data, or roughly 10 million dollars per company.

Flawed insights

Your insights are only as good as your data being analyzed. Inconsistencies, duplicates, misspellings or wrong formats are just some of the ways data can be erroneous. Say you think you have 100 data points, but 20 are duplicates. Obviously, your insights would be flawed. Now imagine you have thousands or millions of rows.

Wasting precious time

Poor data directly impacts organizational efficiency. Your company’s processes, its people, and its goals are all affected when data is not accurate, all compounding and wasting time. When bottlenecks arise, companies have to halt a project to fix a data quality problem. This alone takes months of effort, delaying the efforts and keeping companies in limbo.