Use data flows in Oracle Fusion AI Data Platform to join subject areas, apply quick transformations, and publish curated tables to Oracle Autonomous AI Lakehouse.
For the full product overview and next steps on Oracle Fusion AI Data Platform, check out the resources linked below.
This demo shows how to use data flows in Oracle Fusion AI Data Platform to move curated data to an external Oracle Autonomous AI Lakehouse data source. You will learn how data flows support exporting, curating, and transforming data so teams can share datasets for analysis and AI development using a common lakehouse connection.
The walkthrough starts by building a data flow that combines data from two subject areas: HCM Workforce Core and HCM Performance Management. You select the required columns, add a join on the Person Identifier column, and keep matching rows to create a unified dataset. You then review options to add, select, rename, and transform columns, including changing the Person Identifier data type to an attribute.
Next, you save the output to an existing Oracle Autonomous AI Lakehouse database connection, verify the output table name, and choose whether to replace the existing table data or append to it. After you save and run the data flow, the curated output is written to Oracle Autonomous AI Lakehouse as a new table that can be reused by your team for reporting and downstream analysis.
Please note: Oracle Fusion Data Intelligence (FDI) is now called Oracle Fusion AI Data Platform (FAIDP). All content remains the same, only the product name has changed.
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