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Data Import & Export

How to Automate Excel Analysis and Power BI Reporting by Quarter

Emma BrownEmma Brown Sep 28, 2026 869 views

Question details

The user needs to automate the calculation of percentages and visualize historical trends in Power BI using quarterly Yes/No response data from SharePoint.

Automate Excel Analysis and Power BI Reporting by Quarter
Product
Excel, Power BI, SharePoint
Device & OS
not provided
Scenario
Automating the extraction, calculation, and visualization of quarterly team response data.
Observed behavior
Requires a method to process Yes/No data, retain historical quarters without overwriting, and display trends with team filters in Power BI.
Before you start

Ensure you have the necessary access permissions to the source SharePoint list and that both Excel and Power BI Desktop are fully updated.

Solution 1Recommended

Use Power Query to Automate Data Extraction and Calculations

Connect Power BI or Excel directly to SharePoint using Power Query to automate the transformation of Yes/No data and maintain a historical record.

By utilizing Power Query, you can establish a direct, repeatable connection to your SharePoint data. This ensures that every time you refresh your report, the data processing steps are automatically applied.

1
Connect to SharePoint

Open Power BI Desktop or Excel, navigate to the Data tab, select 'Get Data', and choose 'SharePoint Online List'. Enter your site URL to connect.

2
Add a Quarter Column

In the Power Query Editor, click 'Add Column' and insert a Custom Column to define the reporting quarter based on the submission date.

3
Group Data by Team

Use the 'Group By' feature on the Transform tab to aggregate your data by Team and Quarter, calculating the count of Yes/No responses.

4
Load and Append Data

Load the transformed data into your data model. Ensure your refresh settings in Power BI are configured to append new quarterly data rather than replacing the dataset, preserving your historical records.

Use Power Query to Automate Data Extraction and Calculations
Preserving History: Using Incremental Refresh in Power BI is an excellent way to automatically append new quarter data while retaining all historical records.
Free Microsoft Office alternative

Analyze Quarterly Data Effectively with WPS Spreadsheet

While automated connections to SharePoint rely heavily on the Microsoft ecosystem, WPS Office provides a powerful, free alternative for standard Excel data analysis, pivot tables, and visual reporting.

  1. 1. Open your data file: Launch WPS Spreadsheet and open your exported SharePoint .xlsx file containing the quarterly responses.
  2. 2. Create a PivotTable: Go to the Insert tab and click 'PivotTable' to quickly summarize your Yes/No responses and group them by team.
  3. 3. Visualize Trends: Navigate to the Insert tab, select 'Chart', and choose a Line or Column chart to effectively visualize historical trends across quarters.
100% compatible with Microsoft Excel (.xlsx) file formats.Includes robust PivotTable and charting tools for tracking quarterly trends.Lightweight software that runs smoothly on older devices without lagging.Free to use with a familiar, easy-to-navigate tabbed user interface.
microsoft office alternative - wps office

Frequently Asked Questions

How can I calculate Yes/No percentages in Power BI?

You can calculate percentages by creating a DAX measure in Power BI. Divide the count of 'Yes' responses by the total count of responses using the DIVIDE function, and format the resulting measure as a percentage.

How do I prevent Power BI from overwriting my historical quarterly data?

To preserve historical data, configure Incremental Refresh in Power BI Desktop. Alternatively, use Power Automate to extract the data at the end of each quarter and append it to an ongoing Excel tracking table before importing it into Power BI.

Can I filter my Power BI quarterly trend dashboard by specific teams?

Yes. Add a Slicer visual to your Power BI report canvas and drag your 'Team' column into the Slicer field. This allows viewers to dynamically filter the trend charts and calculations for individual teams.