Data Transforms updates

Run Data Studio Data Load using Data Transforms workflows

You can now define a Data Studio Data Load in a Data Transforms workflow and then execute that data load as part of a Data Flow. You can then schedule the workflow to replay the Data Studio Data Load to capture any updates made to the files and load it into Autonomous Database.

See Define a Data Studio Data Load in a Work Flow for more information about how you can run a Data Studio Data Load in Data Transforms.

Vector Embeddings in Data Flows

Data Transforms now supports the integration of vector embeddings in a data flow using the Oracle Cloud Infrastructure (OCI) Generative AI service. Note that you need to have an Oracle Database 23ai connection to use this feature.

For more information, see Use Text Embedding Vector in a Data Flow.

Use Machine Learning (ML) models in Data Flows

Data Transforms now includes a new data entity type called ML Model. You can use ML Models in a data flow to apply prediction logic on source data and store the output in a target server.

See Machine Learning (ML) Models for more information.

Set Custom Variable Value at Runtime

For data flows and workflows that include variables as part of the flow, when you run the data flow or workflow you can choose to use the default value, the refresh value, or set a custom value at runtime to use for the current run.

See Use Variables in a Data Flow and Use Variables in a Workflow for more information.

Show Queued/Waiting Jobs

The Show Queued/Waiting Jobs option helps improve the overall performance when fetching the list of records to display on the Jobs page.

See the "Search for a Job" section in Create and Manage Jobs for more information.