How to Process a File
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Osmos AI Data Wrangler runs natively within Microsoft Fabric as a Workload. Once added to your organization and user account, the Osmos Workload will be available in your home workspace.
Click here for Quick access to the Osmos Workload.
Once you are logged into Fabric, select Workloads from the side bar.
Select the Osmos Workload to begin cleaning and transforming your file.
Get started by clicking on various available instructions and guides.
To see the workspaces you have access to, click on the link below Workspaces can use
Note: If the Osmos Workload is not present on your home page, either you have not been given access or the Workload has been enabled for your organization
In this step, select the Workspace where the AI Data Wrangler resides.
From the Workload menu or from the Workload sidebar, select your desired Workspace.
From within an existing Workspace, you will see various items such as a Lakehouse, Notebook(s), and one or more AI Data Wranglers.
Click on the AI Data Wrangler you wish to run.
In the Osmos Wrangler, you will select the file(s), you wish to process.
Click on the Choose File icon.
Choose the Lakehouse that contains the source file and hit Connect. Note that the Lakehouse selected will turn light gray when selected.
Select the file(s) and hit Save. The source file(s) will automatically begin to process.
Once you select your file(s), they will be listed on the bottom half of the Workload.
Each file will have a status that updates through the cleaning and transformation.
Statuses include:
Queued
AI Processing
Ready for Review
Completed
Failed
Rejected
Review and Approve your file(s) before writing to the Lakehouse.
Select Ready for Review
To accept and to write to the destination, select Approve.
If you want to dispose of the current process, select Reject. The file will not be written to the destination.
It will update to a Failed Status.
Reasons for rejection may vary. For example, the user initially chose the wrong file to process.
If you select Retry, it will process the file again.
It will not save the outcome of the previous run(s).
The most common scenario for Retry is to incorporate column descriptor updates.
For more info, see Column Descriptors.