How Much Does Bad Data Cost You?

Gartner estimates poor data quality costs organizations an average $12.9 million every year.

But what does it cost your organization specifically and how much lift can you expect from implementing a data quality solution?

This is a surprisingly difficult question to answer. Data teams might track how many data issues they experience and some may even know their average time to resolve those issues, but that is only for the issues that have been caught.

And while it’s easy enough to calculate how much data engineering salary is burned on data quality issues, how do you assess the overall financial risk of data issues that could range in severity from a broken dashboard to reporting wrong numbers to Wall Street?

New Findings From Monitoring 7 Million Tables

By analyzing data from hundreds of data warehouses and more than 7 million tables, we have uncovered key findings to enable data leaders to more accurately assess:

• Data incidents per year
• Total data downtime
• Data downtime labor cost
• Data downtime efficiency cost
• Estimated savings from increased data quality

Use our interactive calculator to instantly get your results and then dive into our workbook to get a deeper understanding of the math, the justification, and how data observability reduces data downtime. Also learn:

• Why organizations underestimate how many data issues they have
• Why the cost of bad data has gone up
• How data observability can not just lower costs but boost revenue
• How to create a build vs buy assessment
• 7 signs it’s time to invest in data quality
• And more!

Access today and take your first step toward impacting your organization’s bottom line.

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