How to Connect Power BI to Multiple Data Sources: A Beginner's Guide
Power BI is an essential tool for creating insightful data visualisations and analyses, particularly when sourcing information from various data sources. For beginners, understanding the prerequisites and learning how to connect to the most common types of data sources is key. This guide covers what you need to know to connect Power BI Desktop to your data, from preparation to execution.
Pre-requisites for Sourcing Data to Power BI Desktop
Before connecting Power BI Desktop to any data source, ensure you have the following:
Access Permissions: Make sure you have the necessary permissions to access the data sources you’ll be connecting to. This might involve read-only access to databases or admin-level permissions for certain online services.
Software Dependencies: Certain connections (e.g., SQL Server) may require drivers or additional software. Confirm that these dependencies are installed and configured properly.
Connecting to Excel Files
Excel files are one of the most used data sources for Power BI due to their simplicity and widespread use.
How to Connect:
In Power BI Desktop, go to ‘Home’ > ‘Get Data’ > ‘Excel workbook’.
Browse your local or network directory to select the Excel file you wish to connect to
Select the worksheet(s) within the Excel file that contains your data.
Click ‘Load’ to import the data directly, or ‘Transform Data’ to open Power Query for data cleansing and preparation.
Best Practice: Ensure your Excel data is formatted as a table, with appropriate column headers and no merged cells for a seamless import.
Connecting to SQL Server Databases
SQL Server is widely used for storing large-scale business data, and Power BI’s native connector simplifies integration.
How to Connect:
In Power BI Desktop, go to ‘Home’ > ‘Get Data’ > ‘SQL Server’.
Enter your Server Name and, if applicable, the Database Name.
Choose your data connectivity mode:
Import for loading data into Power BI
DirectQuery for a direct connection to the data source
Select your authentication method
Click ‘OK’, then choose the tables or views you want to load.
Click ‘Load’ to import the data, or ‘Transform Data’ for customisation in Power Query.
Security Tip: For secure access, ensure data encryption protocols are in place, and use a VPN if connecting to remote databases.
Connecting to Cloud-Based Services (e.g., Google Analytics)
Connecting Power BI to cloud-based services like Google Analytics allows you to blend web performance metrics with other business data.
How to Connect:
In Power BI Desktop, select ‘Get Data’ > ‘Online Services’ > ‘Google Analytics’.
Sign in with your Google account credentials and grant access to Power BI.
Choose the Google Analytics account, property, and view you want to connect.
Select your data set.
Click ‘Connect’ and then ‘Load’ to import the data, or ‘Transform Data’ to open Power Query for data cleansing and preparation.
Other Data Sources
While Excel files, SQL Server, and cloud services like Google Analytics are common starting points, Power BI can connect to a wide range of data sources far beyond these examples. Power BI supports connections to databases like Oracle, MySQL, and PostgreSQL, cloud storage platforms such as Azure Blob Storage and Amazon S3, as well as business applications like Salesforce and Dynamics 365.
For even more flexibility, APIs (Application Programming Interfaces) can be leveraged to connect Power BI to virtually any data source that provides API access. This method is particularly useful for custom or niche applications that don’t have built-in Power BI connectors. By using APIs, businesses can pull data from platforms such as social media services, project management tools (e.g., Asana, Trello), or specialised industry-specific software.
Connecting via APIs typically involves fetching data through web queries using tools like Power Query, where you input API URLs, pass authentication tokens, and define data retrieval methods. This expands Power BI’s ability to integrate with diverse data ecosystems, ensuring comprehensive insights and tailored reporting for your unique business needs.
Transforming Data After Connection
Once connected, leverage Power BI’s Power Query Editor to shape and clean your data:
Remove Unnecessary Columns: Optimise performance by eliminating columns not needed for your analysis.
Add New Columns: Expand the value of your data by merging columns or adding new columns based on values in existing columns.
Rename Columns and Apply Transformations: Ensure data clarity by renaming columns and applying functions like filtering or splitting text, grouping, pivoting, replacing values and many others.
Combine Data from Multiple Sources: Use ‘Merge Queries’ to link tables from different sources with common keys, such as user IDs or transaction dates.
Final Steps: Establishing Data Relationships
Navigate to the Model View in Power BI Desktop to create relationships between imported tables:
Drag and drop fields to define how tables are connected.
Set relationship properties (e.g., one-to-one, many-to-one) to align with your data model.
Connecting Power BI Desktop to multiple data sources - such as Excel files, SQL Server databases, and cloud services like Google Analytics - allows you to consolidate data from different platforms and create powerful visualisations that drive data-driven decisions for your organisation.
Start exploring your data connections today and unlock the potential of Power BI’s comprehensive analysis capabilities.
