Data Analytics takes large quantities of raw, unstructured data from disparate datasets, multiple sources, and systems to draw insights through the application of Artificial Intelligence (AI) resulting in predictive modeling, forecasting, and prescriptive decision-making.
Examples: Used primarily for external clients to pull together a wide range of unstructured or non-uniform data (e.g., large public health data sets, logistics, census information, etc.) for modeling exercises, to find patterns and correlations and transform the data into results or actions
- Data Engineering (Architecture, Modeling and integration (ETL)
- Predictive Analytics (AI, ML) - prescriptive decision-making support
- Descriptive Analytics (Perf. Mgt., self-service ad hoc reports & viz, dashboards)