In this tutorial, we’ll learn how to use an Oracle Fusion Data Intelligence data flow to save curated and transformed data to an Oracle Autonomous AI Lakehouse external data source. By exporting curated datasets to an external database connection, you can make trusted data available for reuse across teams, enabling broader analysis and downstream reporting.
In this video tutorial, you’ll learn how to:
- Combine data from multiple Fusion Data Intelligence subject areas using a join in a data flow.
- Curate data by selecting, transforming, and refining columns before export.
- Configure an Oracle Autonomous AI Lakehouse database connection as the output destination.
- Define output table settings, including table names and data replacement options.
- Validate column characteristics and adjust data types before running the data flow.
- Run the data flow to publish curated data as a reusable table in Oracle Autonomous AI Lakehouse.
By exporting curated data to Oracle Autonomous AI Lakehouse, Oracle Fusion Data Intelligence makes it easier to share trusted datasets for advanced analytics and collaborative reporting across your organization. Watch the full tutorial to learn how to configure a data flow and publish curated data to an external Oracle Autonomous AI Lakehouse data source.
For more information about data flows and exporting data to external database connections, take a look at Oracle Help Center documentation.
Explore the Data Flows in OAC and FDI for Authors Learning Hub module for additional guidance and examples on creating and working with data flows in Oracle Analytics Cloud and Oracle Fusion Data Intelligence.
