Why Automatically Refresh Data in Power BI?
Automatic data refresh ensures that the data displayed in Power BI reports is always up to date. Without regular refresh, reports may contain outdated information, which can lead to poor or incorrect business decisions.
Automatic refresh is especially critical in scenarios where real-time or near real-time data is required, such as monitoring dashboards, alerts, and performance tracking.
Difference Between Manual and Automatic Refresh in Power BI
Power BI supports two main types of data refresh:
- Manual refresh: triggered manually by the user
- Automatic refresh: scheduled or event-driven refresh configured in Power BI Service
Automatic refresh allows organizations to ensure data availability without manual intervention.
| Criterion | Manual Refresh | Automatic Refresh |
|---|
| Frequency | On user request | Scheduled or event-triggered |
| Risk of forgetting | High | Low |
| Responsiveness | Limited | Optimal |
| Workload | Heavier | Reduced |
Use Cases for Automatic Power BI Refresh
Almost every Power BI report requires automatic data refresh. The refresh frequency depends on business needs and data criticality. Some reports require hourly refreshes, while others only need daily updates.
Different Methods to Refresh Data in Power BI
1. On-Demand Refresh
Users can manually refresh datasets directly from Power BI Desktop or Power BI Service.
2. Scheduled Refresh
Scheduled refresh allows you to define a refresh frequency (daily, hourly, etc.) directly from Power BI Service. This is the most common method for automatic refresh.
3. Refresh Using API and External Connectors
You can trigger a Power BI dataset refresh using:
- Power Automate
- Power BI REST API
- External event-based systems (for example, when a new file is uploaded)
Tutorial: Configure Automatic Data Refresh in Power BI
Step 1: Configure the Data Source
For automatic refresh to work, the data source must be accessible from Power BI Service.
If your data source is hosted on-premises, you must install and configure the On-Premises Data Gateway to allow secure communication between Power BI Service and your local data.
Once the application is downloaded and launched, click Sign in, then enter your email address.
Microsoft will then prompt you to sign in. Once this is done, the gateway will appear in the list (remember to refresh the page if it does not). You can then select your newly configured gateway and click Apply to enable the connection between the host computer and the Power BI Service.
Step 2: Define Data Privacy Levels
Before connecting to your data source, configure the appropriate data privacy level (Public, Organizational, or Private) to avoid refresh conflicts.
Click Edit credentials, and you will be taken to this screen:
Select the appropriate setting:
None: No privacy restrictions are applied to the data source, meaning it can be freely combined with other sources without any specific isolation.
Private: The source contains sensitive or confidential data that should not be combined with other sources in order to prevent any information leakage.
Organizational: The source is accessible only within an approved group in the organization and can be combined with other organizational or private sources, but not with public sources.
Public: The source contains data that is accessible to everyone, without restriction, and can be freely combined with other public data sources.
Then click Connect. If it is a cloud resource, you will be prompted to sign in by entering your credentials.
Step 3: Set up a refresh schedule
In the Refresh menu, you can configure the refresh:
Define your refresh schedule
Select your time zone
Enable the Set up a refresh schedule option
Step 4: Enable refresh failure notifications
Once the refresh schedule is set, you can send refresh failure notifications to the semantic model owner (default), as well as to optional contacts (IT department, CIO, etc.).
How to Optimize Data Refresh in Power BI
Data refresh in Power BI is essential to implement for published reports.
Best Practices to Avoid Refresh Errors
To minimize the risk of refresh errors:
- Use stable and reliable data sources
- Regularly update credentials and permissions
- Limit the volume of data to refresh to reduce the risk of failure
Performance Optimization for Large Datasets
Large datasets sometimes require special handling:
- Prefer importing data rather than DirectQuery for very large volumes, unless real-time responsiveness is required
- Use filters to limit the amount of data loaded during each refresh
Monitoring and Troubleshooting Failed Refreshes
Refreshes can fail for various reasons:
- Check the refresh history in Power BI Service to identify the cause of failures
- Enable notifications to be alerted immediately in case of a problem
Common Issues and Solutions for Automatic Data Refresh
Errors can occur at any stage of the process: data sources, gateways, and there are also restrictions and limitations on refreshes in Power BI Service.
Gateway-Related Errors
The gateway may be unavailable, incorrectly configured, or outdated.
Check the gateway status, update it, or reinstall it if necessary (uninstalling the previous version is required).
Connection Issues with External Data Sources
Credentials may have expired or lack sufficient permissions, or the structure of the source may have changed.
In such cases:
- Update credentials
- Verify permissions
- Ensure that the data structure has not changed
Restrictions and Limitations in Power BI Service
Power BI Service has some limitations for refreshes:
- Maximum refreshes per day: 8 for shared capacity, 48 for Premium
- Maximum dataset size: 1 GB for shared capacity, 10 GB for Premium
- Some data sources do not support automatic refresh or require specific configuration
Alternatives and Complementary Tools for Advanced Refresh
Several tools exist to automate data refresh: Power Automate, Power BI API, etc.
Using Power Automate to Automate Refresh
Power Automate can trigger a dataset refresh based on external events (e.g., adding a file to OneDrive, receiving an email, etc.)
It is also possible to integrate a button in a Power BI report to allow users to trigger refresh on demand.
Power BI API: When and How to Use It
The Power BI API provides advanced options to automate and customize dataset refresh.
- It allows triggering refreshes from scripts or third-party applications, ideal for complex integration scenarios
Integration with ETL Tools for Better Data Management
Using ETL (Extract, Transform, Load) tools like Azure Data Factory, Fivetran, or Airbyte helps to prepare data upstream and ensure quality before refreshing it in Power BI.
- These tools can also orchestrate dataset refreshes according to complex business processes
Automatic data refresh in Power BI is essential to ensure the reliability and relevance of your analyses.
By mastering the different refresh methods, optimizing performance, and anticipating common issues, you provide users with continuous access to up-to-date information.
Integration with tools like Power Automate or the Power BI API enables advanced automation scenarios suitable for all business needs.
There is a desktop application to automatically refresh data in Microsoft Power BI Desktop on a regular basis.
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