Welcome back to our Power BI series! In Part One – Getting Started, we dipped our toes into the world of Microsoft Power BI, exploring its capabilities as a business intelligence tool. If you’re just joining us, I recommend checking out the first part to get the basics of Power BI. Today, we’re going to tackle a fundamental aspect of Power BI: connecting to various data sources.
Understanding data connections is crucial for any beginner looking to master Power BI. We’ll explore the different connection types available, discuss how to choose the right one for your needs, and then walk through how to connect to an Excel file using Power BI Desktop. So, grab a cup of coffee, it’s time to switch your brain on!
Understanding Data Connections in Power BI
Before we get into the how-to, let’s talk about why data connections matter. Power BI is all about turning raw data into meaningful insights through compelling data visualisations and interactive dashboards. To do that, you need to bring data into Power BI from somewhere (obviously), and that’s where data connections come in.
Why Connecting to Data Sources Matters
Power BI enables users to access, transform, and analyse data from a hundreds of different sources. Whether you’re pulling data from an Excel spreadsheet, a cloud service, or an on-premises database, the ability to connect to almost any and all of these sources is what makes Power BI such a powerful business intelligence tool.
Types of Data Connections
In Power BI, you have several ways to connect to your data sources. The main connection types are:
- Import Mode
- DirectQuery
- Live Connection
- Composite Models
Let’s break down each one.
Import Mode
Import Mode is the most common way to connect to data in Power BI. When you use this mode, Power BI imports a copy of the data into your Power BI Desktop file (also known as a .pbix file). This mode is great for datasets that aren’t too large and when you need high performance.
- Advantages:
- Fast performance when creating visualisations and reports.
- Full functionality of Power BI features like DAX formulas and data modelling in Power BI.
- Considerations:
- Data can become outdated; you need to refresh to get the latest data.
- Larger datasets can make the file size big and impact performance.
DirectQuery
With DirectQuery, Power BI doesn’t store the data in the .pbix file. Instead, it queries the data source each time you interact with a visual. This is useful when dealing with large datasets or when you need real-time data.
- Advantages:
- Access to up-to-date data without manual refreshes.
- Handles large datasets without bloating your file size.
- Considerations:
- May have performance issues due to constant querying (both on the report and/or it’s data source).
- Limited functionality compared to Import Mode; some DAX functions aren’t available
Live Connection
Live Connection is similar to DirectQuery but is primarily used with SQL Server Analysis Services and Power BI datasets. It allows you to connect to a pre-existing data model without importing or querying the data, so many reports can use the same base data model for reporting and calculation.
- Advantages:
- Centralised data models ensure consistency across reports.
- No data storage in the .pbix file.
- Considerations:
- Can’t create new data models or add new data sources in Power BI Desktop.
- Relies on the data model created by your data team.
Composite Models
Composite Models combine Import Mode and DirectQuery in one model. This gives you flexibility, allowing you to choose the best connection type for different tables within the same model.
- Advantages:
- Flexibility to optimise performance and functionality.
- Ability to use imported data for small tables and DirectQuery for large ones.
- Considerations:
- Can add complexity to your data model.
- Some limitations on relationships between tables.
Choosing the Right Connection Type
So, how do you decide which connection type to use? Here are some factors to consider:
- Data Size: If you’re working with large datasets, DirectQuery or Live Connection might be better.
- Performance Needs: For the best performance, especially when creating complex visualisations, Import Mode is ideal.
- Real-Time Data Requirements: If you need real-time or near-real-time data, DirectQuery or Live Connection is the way to go.
- Functionality: Import Mode offers the full suite of Power BI features, including all DAX functions and data modelling capabilities.
- Data Security and Governance: Consider your organisation’s policies. DirectQuery and Live Connection keep data in the source system, which might be required for compliance reasons.
Understanding these connection types and when to use them is fundamental to effective data analysis in Power BI.
Connecting to Excel Using Power BI Desktop
Now that we’ve covered some of the theory-based knowledge, let’s get our hands dirty and connect to an Excel file using Power BI Desktop. This is a common scenario for many beginners and is a great way to start building your Power BI skills.
Step 1: Open Power BI Desktop
If you haven’t already, download Power BI Desktop from the Microsoft website. Once installed, open the application.
Step 2: Get Data
On the Home ribbon, click on the “Get Data” button. A dropdown will appear with the most common data sources.
Step 3: Choose Excel as Your Data Source
From the dropdown, select “Excel”. If you don’t see it immediately, click on “More…” to see the full list of data connectors available in Power BI.
Step 4: Navigate to Your Excel File
A file browser window will open. Navigate to the location where your Excel file is stored, select it, and click “Open”.
Step 5: Select Data from the Navigator Window
After opening your Excel file, the Navigator window will appear. Here, you’ll see a list of sheets and tables available in your Excel file.
- Select the Tables or Sheets: Check the boxes next to the tables or sheets you want to import.
- Preview the Data: When you select a table, a preview will appear on the right side. This helps ensure you’re selecting the correct data.
Step 6: Transform Data with Power Query
You have two options at the bottom:
- Load: This will import the data directly into Power BI.
- Transform Data: This opens Power Query, where you can clean and transform your data before importing.
I recommend clicking on “Transform Data”. This step is crucial for ensuring your data is clean and structured properly.
Step 7: Clean and Transform Your Data with Power Query
Power Query is a powerful feature that allows you to perform data transformation tasks without altering the original data source.
Common Data Transformation Steps:
- Remove Unnecessary Columns: Right-click on a column header and select “Remove” if you don’t need it.
- Rename Columns: Double-click on a column header to rename it for clarity.
- Change Data Types: Ensure each column has the correct data type (e.g., text, number, date). This is crucial for accurate data analysis.
- Handle Missing Values: Replace nulls or blanks with default values if needed.
- Filter Rows: Remove rows that don’t meet certain criteria.
For example, if you’re working with sales data and only need records from the current year, you can filter out previous years.
Step 8: Apply Changes and Load Data
Once you’re satisfied with the transformations, click “Close & Apply” in the Home ribbon of Power Query Editor.
Power BI will now import the data into your data model.
Step 9: Verify Your Data in Power BI Desktop
Back in Power BI Desktop, you can verify that your data has been loaded
- Fields Pane: On the right side, you’ll see your tables and fields listed.
- Data View: Click on the “Data” icon on the left sidebar to view your data in a table format.
Step 10: Start Creating Visualisations
Now that your data is loaded, you’re ready to create visualisations and build reports and dashboards!
- Report View: Click on the “Report” icon (looks like a bar chart) to start creating visuals
- Drag and Drop Fields: From the Fields pane, drag fields onto the canvas to create charts and graphs.
- Use Power BI’s Visualisations: Choose from a variety of built-in visuals or download custom visuals from Microsoft for more options.
Conclusion
Connecting to data sources is the first step in unlocking Power BI’s potential. Understanding the different connection types—Import Mode, DirectQuery, Live Connection, and Composite Models—helps you choose the best method for your data requirements.
We walked through how to connect to an Excel file, which is a common and straightforward way to get started. With your data in Power BI Desktop, you’re now ready to create insightful data visualisations and dashboards that can drive better business decisions.
Remember, Power BI is a powerful tool that lets users transform raw data into actionable insights. Whether you’re a data analyst looking to enhance your data analytics skills or a beginner just starting out, getting to grips with the many different data connections is a fundamental and crucial step.
Stay tuned for Part Three, where we’ll get more into Power Query and advanced data transformation techniques!
FAQ
Q1: Can I connect to multiple data sources in a single Power BI report?
Absolutely! Power BI allows you to connect to various data sources and combine them in a single data model. This is great for creating comprehensive reports that pull data from multiple places.
Q2: What’s the difference between Power BI Desktop and Power BI Service?
- Power BI Desktop is a Windows application used for data modelling and report creation.
- Power BI Service is the cloud-based platform where you can publish, share, and collaborate on reports and dashboards.
Q3: Do I need a Power BI Pro license to connect to data sources?
No, you can connect to data sources and create reports using the free version of Power BI Desktop. However, to share reports via the Power BI Service, you will need a Power BI Pro licence.
