Industry:

Facilities Management

Problem:

The issue was that Power BI Report took a very long time for the data to refresh from SharePoint Data Source and eventually displayed a timeout error message.

Challenges:

We used SharePoint as a dataset in which we have Over 4 lakh records to create a Power BI report. However, when we refreshed the data to obtain the most recent information from SharePoint to Power BI, the refresh took quite a while, and a timeout error appeared at the end of the process.

Solution:

To address this issue, I implemented a dataflow within the Power BI Service

Steps to Create a Dataflow in Power BI Service:

• Access Power BI Service: Open the Power BI service in a web browser.
• Select Workspace: Select the workspace where you want to create the data flow.

• Dataflow Creation: Click on the New tab and then choose Dataflow Option.
• Define New Tables: Select Define new tables to create a dataflow from the start.
• Choose Data Source: Specify the data source you want to connect to e.g., Excel, SQL Server, SharePoint.
• Select Specific Tables: Once connected, Select and choose the Necessary tables you wish to include in your data flow.
• Transform & Preprocessing: Utilize Power Query Editor to clean, filter, and transform the data for your reports.
• Name Your Dataflow: Assign a name to your dataflow for identification.

In Power BI Desktop, you can use newly created dataflow as a data source for your Power BI reports.

Benefits:

• Faster Refresh: By using a dataflow, you significantly reduced the refresh time from hours to less than a minute.
• Scalability: As your dataset Increases, Dataflows can handle the load efficiently.

Conclusion:

As a conclusion to decrease the refresh time we created a dataflow in Power BI Service which helped the client to minimize the refresh time of Power BI Report from 4-5 hours to barely less than a minute resulting in faster insights and improved efficiency.