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Data Quality, DataOps, and the Trust Blast Radius

A lack of trust will dramatically impact your efforts to become data driven unless you proactively limit the Blast Radius of data quality incidents.

Ryan Gross
Towards Data Science
13 min readJun 26, 2020

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It only takes a small problem to shake someone’s trust in data, but it takes a lot of deliberate effort to make them realize it was just one problem, not a larger issue. The difference in impact is the “Blast Radius” of the problem, and even the most mature data organizations can do a better job minimizing it.

Image Source: US Air Force (via Wikimedia)

Despite the fact that nearly 98% of organizations are making major investments in their ability to become data driven, data quality still costs the average organization $15M per year in bad decisions according to Gartner, and impacts 90% of companies according to Experian . While I covered a few data quality horror stories in a prior article, it isn’t common for a data quality problem to bring down a whole company. Additionally, there are now many modern tools (Soda, ToroData, Trifacta) and practices (primarily DataOps) that are making the application of data quality best practices much easier than they once were.

However, I don’t think I’m going out on a limb to state that Data Quality will never be a solved problem. I also think that the biggest impact, by…

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Towards Data Science
Towards Data Science

Published in Towards Data Science

Your home for data science and AI. The world’s leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.

Ryan Gross
Ryan Gross

Written by Ryan Gross

Emerging Tech & Data Leader at Credera | Interested in how people & machines learn, and how to bring them together.

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