This architecture uses data science and machine learning to analyze streaming and bulk data to provide context and insight for actionable events. A linear sequence of steps spans the diagram:

1. Discover
2. Ingest
3. Transform
4. Curate
5. Analyze, predict, and measure
6. Act

The following components apply to the entire Oracle Cloud Infrastructure region:

• Security, Identity, and Access Management
• Metadata Management
• Discovery Lab and Sandbox

The region is divided into functional layers that house physical or functional components:

• Data Sources layer: Data sources can and will be anything. Those shown include Enterprise Applications, Devices, End Users, and Event Data.

• Data Refinery layer: Raw data passes through the layer.

• Data Persistence Platform layer: Data is collected in object storage and is optionally persisted in Oracle Autonomous Data Warehouse. Data moves from object storage to a block labeled Data Science Cloud in the Data Access layer. Persisted data moves from the data warehouse to Oracle Application Express (APEX) or to the Data Science Cloud in the Data Access layer.

• Data Access layer: Data moves into a block labeled Oracle Application Express (APEX) or into a block labeled Learn (Data Science) where it moves into the Data Consumers layer.

• Data Consumers layer: Consumers of insights include image groups labeled Data Scientists and Applications.