4 data quality challenges that hinder data operations

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.

Read full article at TechTarget’s SearchDataManagement.