Data comes from various sources—databases, cloud services, APIs, and spreadsheets. Power Query simplifies data integration by enabling seamless connections, transformations, and automation in Excel and Power BI.

In this guide, we’ll explore how to connect Power Query to multiple data sources and the best practices for handling them efficiently.

1. What is Power Query?

Power Query is a powerful data extraction and transformation tool used in Excel and Power BI to:

✅ Import data from multiple sources like SQL, SharePoint, APIs, and files.
✅ Transform data by cleaning, merging, and reshaping it.
✅ Automate refreshes for real-time analysis.

Now, let’s explore how to connect Power Query to different data sources.

2. Connecting to Excel and CSV Files

Steps to Connect:

  1. Open Power Query:
    • In Excel: Go to Data > Get Data > From File > From Workbook/CSV.
    • In Power BI: Click Home > Get Data > Excel Workbook.
  2. Browse and Select File: Choose your Excel or CSV file.
  3. Select the Table or Sheet: Choose the worksheet or range to import.
  4. Click Load or Transform: Load directly or modify data in Power Query.

✅ Best Practice: Use Table Format in Excel before importing to maintain data structure.

3. Connecting to SQL Server

Steps to Connect:

  1. Open Power Query and select Get Data > From Database > From SQL Server.
  2. Enter Server Name and Database Name.
  3. Choose the Authentication Mode:
    • Windows Authentication (Default for local servers)
    • SQL Server Authentication (Requires username & password)
  4. Select the Tables or Views to import.
  5. Click Transform Data to modify before loading.

✅ Best Practice: Use Native Queries in Power Query for optimized performance when dealing with large datasets.

4. Connecting to APIs and Web Data

Steps to Connect:

  1. Open Power Query and select Get Data > From Web.
  2. Enter the API URL (e.g., REST API endpoint).
  3. If authentication is needed, choose the correct method (Basic, OAuth, API Key).
  4. Click Connect and select the JSON/XML format.
  5. Use Expand Columns to structure the data.

✅ Best Practice: Use API pagination when working with large API datasets to avoid data limits.

5. Connecting to SharePoint & OneDrive

Steps to Connect:

  1. Open Power Query and go to Get Data > From Online Services > SharePoint Folder.
  2. Enter the SharePoint URL (not the full file link, just the root site URL).
  3. Authenticate using Microsoft Account.
  4. Select and load the desired files.

✅ Best Practice: Use Power Automate to schedule automatic data refreshes from SharePoint.

6. Connecting to Cloud Databases (Azure, Google BigQuery, Snowflake)

Steps to Connect:

  1. Open Power Query and select Get Data > From Azure/BigQuery/Snowflake.
  2. Enter Server & Database Details.
  3. Authenticate using Azure AD, Service Accounts, or API Keys.
  4. Choose the required dataset and transform if needed.

✅ Best Practice: Use DirectQuery mode instead of Import Mode for real-time data analysis.

7. Merging & Appending Data from Multiple Sources

Power Query allows you to combine multiple datasets from different sources for analysis.

A. Merge Queries (Joins)

  • Used to combine related tables (like SQL JOINs).
  • Go to Home > Merge Queries.
  • Select matching columns from both tables.
  • Choose the join type (Inner, Outer, Left, Right).

B. Append Queries

  • Used to stack datasets with identical columns (like UNION in SQL).
  • Go to Home > Append Queries.
  • Select tables to merge and confirm.

✅ Best Practice: Before merging, ensure consistent column names and data types.

8. Automating Data Refresh in Power Query

Once data connections are established, Power Query allows automatic refreshes:

In Excel:

  • Click Data > Queries & Connections > Refresh All.
  • Schedule refresh using VBA macros or Power Automate.

In Power BI:

  • Open Power BI Service > Select Dataset.
  • Go to Scheduled Refresh and set frequency.
  • Use On-Premises Data Gateway for SQL & local files.

✅ Best Practice: Keep refresh frequency aligned with business needs to optimize performance.

Conclusion

✅ Power Query simplifies data extraction and integration from multiple sources.
✅ It supports databases, APIs, SharePoint, cloud storage, and local files.
✅ Using merge, append, and automation, users can optimize data workflows.
✅ Learning Power Query improves efficiency and data analysis capabilities.