Every organization has unique data needs, which require analyses from multiple sources of data beyond what resides in Oracle Cloud Applications. Oracle Fusion Analytics provides a variety of ways to capture this data, from self-service methods to a more governed, curated approach.
Oracle Fusion Analytics provides the following ways to extend with additional data sources.
1. Descriptive flexfield extensions in Oracle Cloud Applications are automatically extend to the Oracle Fusion Analytics data model.
2. Load external data into the same data model as your Oracle Cloud Applications data using Fusion Analytics’ data augmentation connectors* or any data integration tool of your choice. Use the Fusion Analytics’ extension framework to customize the semantic model.
3. Connect to external data sources via native connectors or to data files leveraging the self-service capabilities of the underlying Oracle Analytics Cloud platform.
*See product documentation for supported data sources.
The prebuilt data model and semantic model can be extended and preserved across Oracle Fusion Analytics upgrades.
Fusion Analytics provides data augmentation connectors to extract and load supported data sources (Salesforce, Oracle E-Business Suite, PeopleSoft, Shopify) into the same data repository as your Oracle Cloud Applications data.
See product documentation for supported data sources.
While the prebuilt data model (star schema) for the Oracle Cloud Applications data is read-only to ensure all prebuilt KPIs and analyses are never broken, the data model is easily extended by adding external data sources into custom-built database schemas in the same embedded Oracle Autonomous Data Warehouse service. Fusion Analytics supports any data movement tool for loading data, such as Oracle Data Integration, any third-party tools, or even plain SQL.
The semantic model can be extended using a simple, wizard-driven interface, supporting a multi-user development and publishing process. The following customizations are available:
All semantic model changes follow a test-to-production, version-controlled publishing process. Data engineers/IT can perform extensibility and testing tasks in the provided test environment. Once changes are ready, they can be published to the production environment. All customizations are preserved across Oracle Fusion Analytics upgrades and patches.
There are a variety of ways to include additional data sources to analyses via self-service.
Oracle Fusion Analytics supports more than 50 native connectors to various sources, such as Oracle Autonomous Database, Oracle Fusion Cloud EPM, Google Big Query, Salesforce, and Snowflake. You can also connect to any Java Database Connectivity (JDBC)-based data source. Get real-time data from Oracle Cloud Applications using the Oracle Cloud Applications connector.
Upload personal datasets, such as spreadsheets and comma separated value (CSV) files. Analyse these datasets alone or combine with the prebuilt subject areas of your Oracle Cloud Application data.
Perform all necessary last-mile data preparation and enrichment tasks for analytics with the code-free capabilities of self-service dataflows. Connect multiple data sources, whether in the cloud, on-premises, or personal data extracts, into cohesive datasets on the cloud. Results can be saved in the embedded Oracle Autonomous Data Warehouse, Oracle Analytics storage, any connected RDBMS, or Oracle Essbase.