This diagram shows the conversion of enterprise applications, flat file, events and sensors data from multiple sources through components in an Oracle Cloud Infrastructure region to usable insights for data consumers.

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

• Governance which includes: Data Security (Data Safe, Audit, Logging, Vault) and Data Governance (Data Catalog)
• Infrastructure, Network Security, Identity and Access Management (IAM)

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

• Data Sources layer: enterprise applications, devices, end users, events, sensors, files and any data source to any type. Metadata from the enterprise applications databases is harvested and flows into the block Governance (Data Catalog).

• Ingest, Transform layer: Data is refined in batch and streaming, leveraging different services depending on the use case.

  A block labeled Batch Ingest (OCI Data Integration, Data Integrator, Data Transforms) handles data that is ingested and transformed in batches or micro batches. Raw data is stored in object storage.

  A block labeled Real Time Ingest (GoldenGate Service/OGG Marketplace) handles data that is ingested in near real time. Data ingested in real time is also processed and refined with the capabilities provided by the batch ingest component. Raw and refined application data pass to the Persist, Curate, Create layer along separate paths. Raw data is stored in object storage.

  A block labeled Bulk Transfer (FastConnect, Data Transfer, Storage Gateway, CLI, SDK, API) handles bulk (file) data which then passes on to the Cloud Storage block.

  Streaming data is ingested by a block labeled Streaming Ingest (OCI Streaming, Service Connector Hub, Kafka Connect), which then flows into Cloud Storage (Object Storage), Streaming Processing (OCI Golden Gate, Streaming Analytics) or Streaming Analytics (Golden Gate Stream Analytics).

• Persist, Curate, Create: Data is persisted in the lakehouse in Oracle Autonomous Data Warehouse or Object Storage or both. It is accessed by APIs and is used for analytics, visualization, and data science. Metadata passes to the block labeled Data Governance (Data Catalog).

  Processed data moves into a block within the lakehouse labeled Serving (Oracle Autonomous Data Warehouse). The lakehouse also includes Cloud/Storage/Date Lake (Object Storage).

  Additional processing is provided by Batch Processing (Data Flow, OCI Data Integration, Data Integrator) and by Streaming Processing Ecosystem (Big Data Service)

• Analyze, Learn, Predict layer: Oracle Analytics Cloud uses the data for analytics and visualization. Data Science and AI use data for predictions. Data is served by using OCI Streaming to things and applications. Oracle Functions and Oracle API Gateway provide the data to applications and to IoT consumers.

  This layer includes options such as Visualize/Learn (Analytics Cloud) to provide facts, Learn and Predict (Data Science, OML) to provide predictions, AI Services, Data Enrichment (Data Labeling), and Search (OCI Search).

• Measure, Act layer: People and partners use analytics data while applications and IoT consumers use refined data.