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Migrating Custom Datasets between OAC Environments
In OAC, I have created a custom dataset that uses an OTBI subject area as its data source. I have then used that dataset as my data source for an OAC workbook. When I migrate the workbook from our SIT environment to our UAT environment, the dataset remains connected to the SIT OTBI data source. I then have to go into the workbook and replace the Dev1 dataset with the Dev2 equivalent dataset. Am I doing something wrong? Is there any way to get the workbook migration to see that there is an existing data set from a different source that it could identify and adopt on its own without me having to replace the dataset manually?
Answers
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Hi
It sounds as though you are using dedicated connections for Dev1 and Dev2. If you just had a single OTBI connection, you could update the connection details when you migrate and then reload the data at the dataset level rather than having to create a new dataset and change it in the workbook.
I don't think there is a way of deriving the URL dynamically based on the source like there is in workbooks but I might be wrong.
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Thank you! I'm going to give this a try and see how it goes.
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In OAC, custom datasets are tightly bound to the data connection they were created with (in your case, the OTBI connection in SIT). When you migrate a workbook:
- The workbook migrates cleanly
- The dataset migrates cleanly
- But the dataset keeps the original OTBI connection ID, not just the name
So when the workbook lands in UAT, OAC does not try to:
- Match datasets by name
- Detect “equivalent” datasets
- Rebind the dataset to a different OTBI connection automatically
As a result, the workbook still points to the SIT OTBI-backed dataset, and you’re forced to manually replace it with the UAT one. This is expected product behavior, not a misconfiguration on your side.
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As a workaround, if you don’t need a custom dataset (no joins, transforms, snapshots):
- Build the workbook directly on the OTBI subject area
- Let environment-specific OTBI connections handle themselves
This avoids the dataset layer entirely and migrations become much cleaner.
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