Browse documentation

Run & monitor

Schedule a workflow

Run a saved workflow on a recurring schedule so prepared datasets stay useful as source data changes. Configure the schedule in the Designer, then monitor it from Automation.

Prepare the workflow

Open the workflow, configure its tools and run it once to check the result. If it should publish a reusable dataset, configure its Output destination.

Select Save workflow. Schedules execute the saved workflow, so save changes to its sources, transformations or outputs before the next scheduled run.

Set the recurrence

  1. Select Schedule in the Designer header.
  2. Select New schedule and give it a useful name.
  3. Choose Hourly, Daily or Weekly under Frequency.
  4. Set the minute, time or weekday for that frequency.
  5. Review Timezone, then select Save Schedule.

The timezone starts with your browser's detected zone. Use an IANA name such as Asia/Kolkata or America/New_York. After saving, check the server-confirmed next run time.

The advanced controls support a cron expression when you need a more specific recurrence. Schedule frequency and active-schedule allowances follow your workspace plan.

Monitor recurring work

Open Automation to see your workspace's schedules, associated workflows, status, next run, last run and duration. Open the last run to inspect its execution details.

Use Run now when you want to execute a schedule immediately. Pause a schedule to suspend future automatic runs, then activate it when the workflow should resume.

To adjust its recurrence, open the workflow in the Designer and edit the schedule from Schedule. New Schedule on the Automation page helps you select a workflow and open its Designer.

Review a failed or partial run

Open the run details to identify the affected step or output. Check the source connection, tool configuration and output destination, then save any workflow changes and use Run now to try again.

For a workflow that produces several outputs, confirm the outputs you need completed and were saved successfully. The last successful dataset version remains available if publishing a replacement fails.