How to Refresh Dataset in Power BI

To refresh a Dataset in Power BI, follow these easy steps: 

Understanding data refresh in Power BI involves knowing that whenever you initiate a refresh, Power BI queries the underlying data sources, loads the data into a semantic model, and updates any visualizations in your reports or dashboards. The process varies depending on the storage modes of your semantic models. 

 

Storage Modes and Semantic Model Types: Power BI supports different storage modes and semantic model types, each with unique refresh requirements. You can either reimport data to reflect changes or query data directly from the source. 

 

Power BI Refresh Types: There are several types of refresh operations, including data refresh, OneDrive refresh, query cache refresh, tile refresh, and report visual refresh. Power BI automatically determines the necessary steps based on the semantic model, but understanding these types helps to grasp the complexity and duration of a refresh operation. 

 

Storage Modes: Power BI semantic models can operate in one of the following modes: 

  • Import mode
  • DirectQuery mode
  • LiveConnect mode
  • Push mode 

 

Data Refresh: Typically, refreshing data in Power BI means importing data from the original sources into the semantic model, either on a set schedule or on-demand. This can be done multiple times a day, especially if the data changes frequently. On shared capacity, up to eight scheduled refreshes are allowed per day. On Premium capacity, up to 48 scheduled refreshes are allowed, with unlimited refreshes possible through the XMLA endpoint using TMSL or PowerShell. 

 

OneDrive Refresh: If your semantic models and reports are based on files stored on OneDrive or SharePoint Online, Power BI performs a OneDrive refresh to synchronize the files about every hour. This type of refresh is different from a semantic model refresh and is based on the file’s item ID in OneDrive. 

 

Data Infrastructure Dependencies: Successful data refresh requires accessible underlying data sources. Depending on whether your data sources are on-premises, in the cloud, or a combination of both, you may need to configure a data gateway to enable refresh schedules or on-demand refreshes. 

 

Refresh and Dynamic Data Sources 

A dynamic data source is one where some or all of the connection information is determined when Power Query runs its query. Examples include the instance name and database of a SQL Server, the path of a CSV file, or the URL of a web service. 

In most cases, Power BI semantic models using dynamic data sources can’t be refreshed in the Power BI service. Exceptions include using the RelativePath and Query options with the Web.Contents M function, or queries referencing Power Query parameters. 

To determine if your dynamic data source can be refreshed, open the Data Source Settings dialog in Power Query Editor and check for warning messages in the Data Sources In Current File section. 

 

Configure Scheduled Refresh 

Setting up connectivity between Power BI and your data sources is the most challenging part of configuring a data refresh. Afterward, you simply set the refresh schedule and enable failure notifications. For detailed instructions, see the guide on Configuring Scheduled Refresh. 

 

Setting a Refresh Schedule 

In the Scheduled refresh section, define the frequency and times for refreshing your semantic model. On shared capacity, you can set up to eight daily refreshes, and on Power BI Premium, up to 48. After configuring the schedule, the settings page will inform you of the next refresh time. To test your configuration, you can perform an on-demand refresh without affecting the next scheduled refresh. 

Keep in mind that the actual refresh might start within 15 minutes of the scheduled time but can be delayed by up to an hour. 

 

Best Practices 

Regularly check the refresh history of your semantic models to ensure your data is current. Address any issues promptly and coordinate with data source owners and gateway administrators if necessary. Here are some additional recommendations: 

  • Schedule refreshes during less busy times to avoid overloading resources. 
  • Consider using DirectQuery/LiveConnect mode for frequently changing or large datasets, but be aware of their limitations. 
  • Verify that your refresh time doesn’t exceed the maximum duration. For large models, consider using Incremental Refresh. 
  • Optimize your semantic models to include only necessary tables and columns and avoid dynamic data sources and complex DAX calculations. 
  • Ensure privacy settings in Power BI Desktop match those in the data source definitions after publishing. 
  • Limit the number of visuals on dashboards to improve refresh performance. 
  • Use reliable enterprise data gateway deployments and separate gateways for Import and DirectQuery/LiveConnect models. 
  • Ensure Power BI can send refresh failure notifications to your mailbox. 

 

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