A Guide To The 4 Types of Data Analytics: Descriptive, Predictive, Prescriptive, and Diagnostic Analytics
Blog post from Sigma
The evolution of cloud technology has revolutionized data analytics, enabling organizations to leverage large data sets quickly and efficiently through platforms like Snowflake and Amazon RedShift. This transformation allows companies to engage in four types of analytics: descriptive, diagnostic, predictive, and prescriptive, each offering unique insights. Descriptive analytics focuses on past events through data aggregation and visualization, while diagnostic analytics explores the reasons behind these events using techniques like correlation and drill-down analysis. Predictive analytics uses statistical modeling and machine learning to forecast future outcomes, enhancing decision-making and risk management. Prescriptive analytics, although less commonly used, suggests actionable steps based on predictions, requiring human interpretation to generate meaningful insights. Modern tools like Sigma facilitate these analytics processes, making them accessible to non-technical decision-makers and democratizing business intelligence by providing critical insights for performance improvement and strategic planning.