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Tag: bad data

Data Quality Study Reveals Business Impacts of Bad Data

If your data warehouse is starting to look like Miss Havisham’s decaying mansion, you may have a data quality problem. A new survey of 500 data professionals from open source data quality tool Great Expectations rev Read more…

Monte Carlo Hits the Circuit Breaker on Bad Data

Data pipelines are critical conduits of information for data-driven companies. But what happens when the data in the pipeline becomes corrupted? In some situations, you want to immediately stop the flow of data, which is Read more…

The Search for Better COVID Data Is Not Over

From a public health perspective, the past 23 months have been, shall we say, eventful in the United States. More than 70 million Americans have contracted COVID-19, according to the Johns Hopkins coronavirus tracker, an Read more…

What We Can Learn From Famous Data Quality Disasters in Pop Culture

Bad data can lead to disasters that cost hundreds of millions of dollars or — believe it or not — even the loss of a spacecraft. Without processes that guard the integrity of your data every step of the way, your Read more…

Do You Have Customer Data You Can Trust?

Customer data is the new business success factor, yet over 76% of the 4,500+ companies we’ve worked with did not have accurate customer data. Surprised? Here’s more. Forty-seven percent of these companies did not Read more…

As Data Quality Declines, Costs Soar

The bigger the data, it appears, the better the chances much of it will be "bad" data. And that bad data is costing companies a bundle, according to research published in MIT Sloan Management Review. "Bad data is t Read more…

Is Bad Data Costing You Millions?

It’s no secret that harnessing the power of big data has the potential to be a huge boon for enterprises. Scores of analyst reports offer the promised land of predictive analytics and countless other benefits, making t Read more…

Five Steps to Fix the Data Feedback Loop and Rescue Analysis from ‘Bad’ Data

Despite enterprises’ best intentions in enforcing top-down standardization of data sets, non-compliant data can easily seep in and, through aggregations, transformations, and standardizations, spread throughout the org Read more…

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