An analytical workload is a broad collection of computing tasks that analyze a particular business process, market condition, user behavior, prediction, forecast, simulation, and myriad other use cases. Today’s analytical systems are designed to handle greater data volume, data complexity, unpredictability, velocity and variety. An analytical workload is created by users who are exploring data in real time, and delivers data and insights to a broad set of tools, dashboards, and data applications.

An analytical workload is valuable when users need to conduct analyses like response attribution, churn prediction and fraud detection. Its flexibility means that data can be looked at in various ways while still drawing correlations and predicting future possibilities from sophisticated models.

Today’s analytical workloads often analyze very large datasets. That’s important because more data than ever before is being collected by organizations, including user behavior, statistical analysis and IoT (Internet of Things) information.