What is Diagnostic Analytics?
Diagnostic analytics is a form of advanced analytics that examines data or content to answer the question, “Why did it happen?” By using diagnostic analytics, companies can gain insights into the causes of patterns they’ve observed in their data. Diagnostic analytics can involve a variety of techniques, including drill-down, data discovery, data mining and correlations. To investigate the root cause of trends, companies may need to examine additional data sources, potentially including external data. Diagnostic analytics enables companies to make more-informed decisions about how to remediate problems and drive continued success.
A drawback of diagnostic analytics is that it focuses on historical data; it can only help businesses understand why events happened in the past. In addition, further investigation may be needed to determine whether the correlations revealed by diagnostic analytics really show cause and effect. To look into the future, businesses need to use other analytic techniques, such as predictive analytics, which examines the potential future impact of trends and events, and prescriptive analytics, which suggests actions businesses can take to influence the outcome of those future trends.