Data quality is key for any organization utilizing data for operations, and it starts with mitigating data quality challenges that lead to inaccurate or misleading analytics results.
Seventy-seven percent of 500 information services and data professionals said they had issues with data quality, and 91% said that data quality issues were affecting company performance, according to a survey conducted earlier this summer by Pollfish on behalf of open source data tool Great Expectations.
Last year, poor data quality directly cost the average organization $12.9 million a year, Gartner estimated. It increases the complexity of data ecosystems and leads to poor decision-making.
