Four Ways Bad Data is Bad for Business

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More businesses today are realizing the power of leveraging data for competitive advantage. But for data to be a true business driver, the data needs to be something that business users can easily find and trust to feel confident in using the data for business insight and analysis.

Too many companies struggle with this issue and instead waste precious time looking for the data they need and spend trillions of dollars (up to $3.1 trillion according to HBR) doing so, only to come up short. The reality is the data is buried in different systems and/or departments across the organization. And when the business users and data scientists looking for data are able to find it, they may have difficulty identifying where the data came from, understanding how it’s been changed over time, whether they’re allowed to use it and/or if it’s the right data in the first place. This can lead to bad business decisions that can adversely affect the organization’s bottom line.

The infographic below from our friends over at Collibra outlines four ways bad data can be bad for business: wasted time; failed business intelligence initiatives; strategic missteps; botched priorities; and how organizations can avoid this bad data trap through strategies such as data governance and data catalog to make the most out of their BI initiatives.



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  1. What a great way to explain how dirty data can cost a business. There are many more ways, like bad data in a health organization can actually (and has) to lead to patient harm. Part of Data Governance is cleaning the bad or dirty data. There are a lot of tools out there like this one from Data Ladder:, you can even sign up for a free trial!