Analytics Requires Trusted and Ethical Use of Data and AI/ML
Analytics are critical to the efficient and effective operation of most modern organizations; to that end, trusted analytics require trusted data. Inaccurate and untrustworthy data means organizations cannot rely on the analyses produced using that data. Trustworthiness requires accurate, high-quality data, but also appropriate use of the data that complies with an organization’s access and risk management policies. High-quality data enables high-quality decisions, but with the ever-growing volume of data flowing within organizations, conducting quality control can be extremely labor-intensive. Nearly two-thirds (64%) of organizations in our research report that ensuring the quality of their data is one of the tasks where they spend the most time, second only to preparing data for analysis.