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"One of the biggest flaws in organizational use of data is confusing correlation with causation. As more companies embark on “big data” journeys, employees who are not necessarily trained in statistics or data science are being asked to analyze data. And when untrained people spot correlating factors, they often confuse the correlating variables with cause and effect. Compounding this issue is that access to dashboards and models with the intent of driving data-based decisions is widely granted. But easy access to data does not mean those with access have the proper background to be reading the data correctly. Organizations must employ workers who are trained in statistics, actuarial science, or data science — or provide the proper education to those who are not—to make sure the truth is reported."