A new release for Data Integration is now available!
You can now:
- Create a task to schedule and run an Oracle Cloud Infrastructure Data Flow application from within Data Integration.
- Use a pivot operator and aggregate function expressions to transform unique row values from one attribute into multiple new attributes in the output.
- Specify the action to take when no matching row is found or when multiple matching rows are found in the lookup source for a lookup operator.
- Use a function operator to invoke Oracle Cloud Infrastructure Oracle Functions from within a data flow in Data Integration.
- Use a SQL statement to define the source and shape of an Oracle Database data entity.
- Use hierarchical data and complex types in Oracle Object Storage source and target data entities.
- Fetch the latest schema metadata of existing target and source data entities while working on a data flow.
- Select attributes to be excluded from output data when creating an expression in the Expression Builder.
- Use a single output file for the target of an Oracle Object Storage data entity.
- Create a project that includes data flows in a samples folder.
- Move data flows, pipelines, and tasks from one project or folder to another project or folder in the same workspace.
- Save as a copy the data flow, pipeline, or task you are creating or editing.
- View workspace and Application statistics such as uptime, amount of data processed, and the number of task runs by status within a date and time range.
- View and analyze task run details. You can:
- Filter the list of task runs in an Application by a task type and a run status.
- Compare the performance of two task runs of the same task type.
- View the parameters and configured values used in a task run.
- View the duration of a task run and the amount of data processed, and compare the current details with statistics from up to five previous runs.
- View a pipeline graph with a pipeline task run. In the graph, you can see path and run statuses of tasks and activities from start to finish.
For details, see Data Integration.