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|**Scheduled Refresh**| Automatically refreshes data at specified intervals to keep it up-to-date. This allows you to automatically refresh the data at specified intervals, ensuring that the data in the new stage is always up-to-date. | - Can be configured to run multiple times a day.<br>- Ensures data in the new stage is always current. |
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|**On-Demand Refresh**| Allows immediate data refresh, triggered manually or programmatically.| - Can be done through workspace list or lineage views.<br>- Can be triggered via a pipeline containing a dataflow activity.|
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|**Incremental Refresh**| Refreshes only the data that has changed since the last refresh, improving efficiency. Click [here to understand more about incremental refresh](https://github.com/brown9804/MicrosoftCloudEssentialsHub/blob/main/0_Azure/2_AzureAnalytics/0_Fabric/demos/11_PBi_IncreRefresh.md)| - **Evaluate Changes**: Checks for changes in the data source based on a DateTime column.<br>- **Retrieve Data**: Only changed data is retrieved and loaded.<br>- **Replace Data**: Updated data is processed and replaced. |
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|**On-Demand Refresh**| Allows immediate data refresh, triggered manually or programmatically.| - Can be done through workspace list or lineage views.<br>- Can be triggered via a pipeline containing a dataflow activity.|
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|**Incremental Refresh**| Refreshes only the data that has changed since the last refresh, improving efficiency. Click [here to understand more about incremental refresh](../PBi-IncrementalRefresh.md)| - **Evaluate Changes**: Checks for changes in the data source based on a DateTime column.<br>- **Retrieve Data**: Only changed data is retrieved and loaded.<br>- **Replace Data**: Updated data is processed and replaced. |
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Steps to Set Up Incremental Refresh:
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1.**Create or Open a Dataflow**: Start by creating a new Dataflow Gen2 or opening an existing one.
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