Lesson 2: Getting Data into Power BI Desktop

Introduction

Objective: In this lesson, you will learn how to navigate the Power BI Desktop interface and import data into Power BI. We’ll explore the main components of the Power BI Desktop user interface – including the ribbon menus, the Fields pane, the Visualizations pane, and the Filters pane – and explain their purposes. We will also highlight key commands such as Get Data, Save, and Publish. By the end of this lesson, you should feel comfortable finding your way around Power BI Desktop and performing basic actions like loading data and saving or publishing your work.

We’ll use a simple case study throughout this lesson: a CSV file of sales transactions. Imagine we have a small dataset of retail sales (orders with dates, customer names, prices, quantities, etc.) – this will be our example to practice getting data into Power BI and building a report. (The sample dataset is provided for download at the end of this lesson.)

Navigating the Power BI Desktop Interface

When you first launch Power BI Desktop, you’re greeted with a report editor interface consisting of several sections: a top ribbon menu bar, a central report canvas, and panes on the right side for Fields, Visualizations, and Filters[3]. Below the canvas, you will see page tabs for navigation if your report has multiple pages. Let’s tour these one by one:

• Ribbon Menus: The ribbon at the top of Power BI Desktop contains all the major tools and commands, organized into tabs (similar to Microsoft Office applications)[2][7]. For example:

  • The File menu (accessible from the left of the ribbon) lets you create new reports, open files, and perform file operations like Save, Save As, and Publish[2]. This is also where you’ll find Options and Settings and account info.
  • The Home tab is the primary tab for report creation. It includes common actions such as Get Data (to import data from various sources), Transform Data (to clean or shape data in Power Query), Publish (to publish your report to the Power BI service), and clipboard operations (Cut, Copy, Paste)[2][2]. You’ll likely use the Home tab frequently.
  • Other tabs like Insert, Modeling, View, Optimize, and Help group more specific tools (for adding visuals or buttons, managing relationships and measures, toggling visual options and themes, performance analyzer, getting help, etc.)[7]. For example, the Insert tab contains options to add text boxes, shapes, images, or new visuals to the canvas[7], while the Modeling tab provides data modeling functions (like creating relationships or calculations)[7]. Explore each ribbon tab to see the commands available – the ribbon is context-aware, so some buttons appear only when relevant (for instance, when a visual is selected)[3].

• Report Canvas: This is the large blank area in the center where you build your reports. It’s like a design surface or canvas for creating data visualizations. When you add charts, tables, or other visuals, they appear on the canvas. Each page of your report has its own canvas; you can navigate pages using the tabs at the bottom[3]. For example, if you have Page 1 and Page 2, you can click the tabs to switch between them. The canvas is where you will drag fields and create visuals (we’ll do this shortly in the example).

• Fields Pane: Located on the right side, the Fields pane lists all the tables and columns (fields) in your data model[2]. When you load data into Power BI, each dataset (or each table in a dataset) will appear here. This is your primary tool for selecting and managing the data you want to use in your visualizations[2]. You can expand a table to see its fields (columns) and measures. From the Fields pane, you can drag and drop fields onto the canvas or into visualizations to build charts and tables. For example, dragging a numeric field like Sales Amount onto the canvas will create a default chart (perhaps a column chart of sum of sales) on the report canvas[2]. You can also search within the Fields pane to quickly find a field by name if you have many fields[2]. (Note: In the latest Power BI versions, the Fields pane may also be labeled as the “Data” pane – it serves the same purpose of showing your available data fields[7].)

• Visualizations Pane: Positioned next to the Fields pane, the Visualizations pane allows you to choose and customize the type of visual for your data[2]. It contains a gallery of visual icons (such as bar chart, line chart, pie chart, map, table, etc.) that you can click to add that visual to the canvas[2][7]. When you select a visual on the canvas, this pane also displays customization options: you’ll see fields wells (to add data to different parts of the visual, like axes or values) and format options (to adjust colors, axes, labels, etc.). You can switch a chart’s type here or format its appearance. For instance, if you have a chart selected, the Visualizations pane will show icons for “Build visual”, “Format visual”, and “Analytics” (for certain visuals) allowing you to toggle between designing the content, formatting the styling, or adding analytic features[3]. In summary, the Visualizations pane is where you pick a visual type and then drag fields into the visual’s slots (or onto the canvas) to populate it with data[7]. You can also import custom visuals if needed, but that’s beyond our current scope.

• Filters Pane: Beneath the Visualizations pane (also on the right side) is the Filters pane[2]. This pane lets you apply filters to limit or refine the data shown in your report. Filters can be applied at three scopes: report-level (effecting all pages and visuals), page-level (only the current page), or visual-level (only a specific chart or visual)[2]. For example, you might set a report-level filter to show only data for the current year across all pages, or a visual-level filter to show only a particular product’s data in one chart. You add filters by dragging fields into this pane and specifying the filter criteria (e.g., drag “Region” into Filters and select one or more regions to filter by). The Filters pane helps users focus on specific subsets of data – for instance, filtering a sales chart to a certain region or date range[2]. Power BI also supports slicers (visual filter controls) and cross-filtering by clicking on visuals, but the Filters pane is where you set persistent filters that remain in effect until changed. One advantage of using the Filters pane is that the filter selections can be saved with the report, ensuring viewers see the filtered view by default[3]. (Tip: If your Filters (or Fields/Visualizations) pane is not visible, it might be collapsed – you can expand or collapse these panes using the small arrows at the top of each pane[7] to give more room to the canvas.)

• Pages and View Switcher: Along the bottom of the canvas, you’ll find the page navigation tabs (Page1, Page2, etc.) for multi-page reports[2]. You can add a new page with the “+” icon, rename pages by right-clicking the tab, or reorder them as needed[2]. Also, on the very left side of Power BI Desktop, there are icons for Report, Data, and Model views[8][7]. By default, you’re in Report view (where you build visuals). The Data view shows your data in tabular form (useful for inspecting data or creating calculated columns). The Model view shows a diagram of your tables and relationships (useful for managing how tables relate to each other)[7]. For this lesson, we will stay in Report view.

Now that we know our way around the interface, let’s use these components with an example dataset.

Case Study Example: Sales Transactions Dataset

To illustrate the process of getting data into Power BI, we will use a sample sales transactions dataset. This is a simple Excel file representing, say, a small store’s sales orders. It contains a single table with the following columns[6]:

• Order No. – A unique identifier for each order (e.g., 1001, 1002, 1003, …).
• Order Date – The date on which the order was placed by the customer.
• Customer Name – The name of the customer who placed the order.
• Shipment Date – The date the order was shipped to the customer (usually a few days after the order date).
• Retail Price – The price of the product sold (per unit).
• Order Quantity – The number of units/items ordered.
• Tax – The tax amount on the order (for example, sales tax on the purchase).
• Total – The total amount paid for the order, including tax (typically, Total = Retail Price * Order Quantity + Tax)[6].

This dataset is small and fictional, but it’s perfect for practice. It allows us to do things like add up total sales, count orders, filter by date or customer, etc., in Power BI. Here’s a quick preview of what the data might look like (first few rows):

We will now walk through bringing this data into Power BI Desktop and exploring it with a simple visual.

Download the Example Dataset:

For your practice, you can download the Sales Transactions sample data as an Excel/CSV file. Use the link or save the following CSV data into a file (e.g., SalesData.csv) to follow along in Power BI


(This dataset is a simple fictitious example meant for instructional use. The numbers are for demonstration.)

Importing Data into Power BI (Using Get Data)

Now, let’s import the sales transactions data into Power BI Desktop and see it in action. We will go step-by-step:

1. Launch Power BI Desktop and close the start screen if it appears (you’ll then see a blank report canvas and the interface we described earlier). Ensure you are in Report view (the default view).

2. Click on Get Data on the Home ribbon[2]. This will open the Get Data dialog, where Power BI shows the various data source options. Power BI can connect to many types of data sources (Excel files, CSV files, databases like SQL Server, cloud services, etc.)[2].
   In our case, since the sample data is in CSV format, choose  “Text/CSV” if you have it as a CSV file).

3. Navigate to the file on your computer in the Open dialog and select it. Power BI will then connect to the file and show a Navigator window. In the Navigator, you’ll see a list of tables or sheets found in the workbook. For our example, select the sheet or table that contains the sales data (for instance, it might show a sheet name like “SalesData”). You can click the check box for the table. Below, a preview of the data will appear so you can verify you’ve got the right data.

4. Load the data: In the Navigator, click the Load button to import the data into Power BI. (If you needed to clean or transform the data first, you could click Transform Data, which opens Power Query Editor. But for this simple example, our data is already clean, so loading directly is fine.) After clicking Load, the Navigator will close, and you might see a progress bar as the data is imported. Once done, the Fields pane on the right will populate with a table representing your dataset (e.g., it might be named after your file or sheet, such as SalesData). Congratulations – you have brought data into Power BI!

   • Verifying the Data: Expand the Fields pane table to see all the fields (Order No, Order Date, Customer Name, etc.) now listed[2]. This confirms the data was loaded correctly. You can also switch to the Data view (click the table icon on the left) to see the actual data rows if you want to inspect them in Power BI Desktop’s grid. But staying in Report view, we can proceed to use the data in a visual.

5. Create a quick visualization: Let’s do a simple exercise to get comfortable. We will create a basic visualization to answer a question like “How many total sales (Total amount) by customer?”.
   On the Report canvas, click on an empty space, then in the Visualizations pane select a Column Chart visual (the clustered column chart icon). An empty chart frame will appear on the canvas. Now, in the Fields pane, expand the table and check the box next to Customer Name – this will add Customer Name to the chart’s axis automatically. Next, check the box next to Total – this will add the Total sales as the value. Instantly, Power BI creates a column chart showing total sales for each customer in the dataset[1]. Each bar represents a customer, and the height is the sum of order totals for that customer. You have just built your first Power BI visual!

   • Alternatively, try simply dragging Customer Name from the Fields pane and dropping it into the “X-axis” or “Category” field well of the visual, and dragging Total into the “Y-axis” or “Values” field. The result is the same – Power BI aggregates the Total for each customer and displays the chart. If you drag a field directly onto the canvas (not onto an existing visual), Power BI will by default create a new visual for you. For example, dragging the Order Date field onto the canvas might create a table or chart of dates. Power BI automatically chooses a visualization type based on the data (you can change it afterward)[2].

   • Customize (optional): You can experiment with the chart formatting. For instance, click on the chart, then in the Visualizations pane select the Format (paintbrush) icon to change colors or data labels. But formatting details can be covered later; our focus here is just to ensure the data is in and a simple visual is working.

6. Using Filters: Try out the Filters pane by applying a filter to the visual or the page. For example, if you want to see sales for only a specific date range, drag the Order Date field into the Filters pane under “Page level filters.” Then, you can select a range of dates. The chart (and any other visuals on the page) will update to reflect the filter. Similarly, you could drag Customer Name into Filters and filter to one or two customers. This shows how the Filters pane can refine your analysis view[2]. (We won’t go in-depth on filtering here, but remember that filters can be set per visual, per page, or for the whole report.)

At this point, you have successfully navigated the interface and imported data into Power BI Desktop. We used the Get Data feature to load an Excel file, saw the data appear in the Fields list, and created a simple visualization by dragging fields onto a chart. We also identified where key actions like Save and Publish are – which we’ll do next.

Saving and Publishing Your Work

As you build your report, remember to save your Power BI Desktop file. Power BI Desktop files are saved with a .pbix extension, which contains your data model, visuals, and all report elements.

• Save the Report: Go to File > Save (or click the Save icon on the Quick Access Toolbar) to save your work[2]. Choose a location and name for the file (for example, SalesAnalysis.pbix). After saving, if you make further changes, an asterisk “*” will appear in the title bar next to the file name until you save again – indicating there are unsaved changes[2]. It’s a good habit to save periodically.

• Publish to Power BI Service: If you want to share your report or access it online, you can publish the .pbix file to the Power BI cloud service (assuming you have a Power BI account). On the Home ribbon, click the Publish button[2][2]. You’ll be prompted to sign in to Power BI if not already. Then choose a workspace (the online location) to publish to. Once published, your report will be accessible in the Power BI service, where you can create dashboards or share it with others. For this lesson’s scope, publishing is optional – but it’s the step that makes your report available beyond the desktop application. (Note: The Publish feature requires internet and a valid Power BI license for sharing with others.)

If you do publish the report, you can log into the Power BI service (powerbi.com) in a browser to view it. Remember that if you update the report in Power BI Desktop later, you would need to hit Publish again to send the updated version to the service.

Best Practices for Organizing Data in Power BI Desktop

As you start working with data in Power BI, here are some best practices and tips to keep your reports well-organized and your data model efficient:

• Use Meaningful Names: Rename your tables and fields to business-friendly names. This makes it easier to understand the data when creating visuals. For instance, if your Excel sheet was named “Sheet1”, you can double-click it in the Fields pane and rename it to “Sales Data”. Similarly, ensure fields have clear names (e.g., “Total Sales” instead of a cryptic name). This clarity helps especially when you have multiple datasets. (Power BI’s modeling view or the Fields pane allows you to rename tables/fields easily[2].)

• Organization of Visuals: Keep your report canvas organized. Align visuals neatly and use titles, labels, and possibly text boxes to annotate sections of your report. A well-organized report is easier to read and understand. 

• Performance Considerations: For larger data sets, try to import only what you need for analysis to keep the report efficient. Power BI can handle large data, but unnecessary columns or very detailed data might slow things down. Aggregating data in queries or filtering out irrelevant data before loading can help.

• Save Versions: It’s not a data model tip per se, but a project management tip: keep versions of your Power BI file if you’re making significant changes (or use source control if available). This way you can revert if something goes wrong in a complex editing session.

By following these practices you’ll make your Power BI development smoother and your reports more understandable. Power BI Desktop is quite intuitive once you spend some time with it, and these habits will reinforce that.

Common Challenges and Tips for Beginners

As a new Power BI Desktop user, you might encounter a few challenges. Here are some common ones and how to address them:

• Overwhelmed by the Interface: At first, all the options in the ribbon and multiple panes can feel overwhelming. Don’t worry – you don’t have to use every feature at once. Start with the basics: loading data and creating a couple of simple visuals (as we did). With practice, the interface will become familiar. The ribbon’s layout is similar to Excel, so many commands (Save, Copy/Paste, etc.) work as expected. Use the search bar in the ribbon if you can’t find a command – it can quickly locate functions for you[5].

• Fields/Visualizations Pane Disappeared: If you accidentally close or hide a pane, it can be confusing. Remember you can toggle the Views of these panes from the View ribbon or by clicking those little arrow icons. For instance, if the Fields pane is hidden, clicking the “>>” arrow on the right edge will expand it. Also, ensure you’re in Report view; in Data view, you won’t see the Visualizations pane (that’s normal). If needed, go to View > Reset Panes to default layout.

• Data Types and Formatting: Sometimes a field might not behave as expected – e.g., a date is treated as text, or a number isn’t summing. Check the Data view: you can set a field’s data type (text, decimal, date, etc.) and formatting. For example, ensure Order Date is a Date type (so you can use date hierarchies and proper sorting). If you see * (sigma) symbols next to a field in the Fields list, it indicates numeric fields that can aggregate; ABC icon indicates text fields, calendar icon for dates, etc. If something has the wrong type, use Transform Data to fix the column type and reload.

Remember, these challenges are a normal part of learning. The key is to experiment and use resources available when you get stuck.

Additional Resources for Learning Power BI Desktop

Power BI is a rich tool, and there is a lot more to learn beyond this introductory lesson. Fortunately, many resources are available to help you deepen your understanding:

• Microsoft Learn Documentation: Microsoft provides comprehensive official documentation and guided learning paths for Power BI. You can read topics like “Getting Started with Power BI Desktop”, “Connecting to Data Sources”, “Creating your first Power BI report”, and more. The documentation often includes step-by-step tutorials and videos. For example, Microsoft’s “Tour the Power BI report editor” article walks through the interface in detail[3][3], and there are specific guides on using features like the ribbon, visuals, and filters. Explore the Microsoft Learn site’s Power BI section for free tutorials and concept explanations.

• Power BI Community and Forums: The Power BI community forums are very active. You can search for questions or ask your own if you run into issues. Chances are, whatever problem you encounter, someone has asked it before. Microsoft’s community site and stack overflow are good places to search for solutions or best practices.

• Video Tutorials and Courses: Many free videos (on Microsoft’s channel or platforms like YouTube) walk through Power BI basics. Watching an instructor build a report can be immensely helpful. Microsoft often holds webinars and events (Ignite, etc.) where new features are explained – recordings are usually available online.

• Sample Reports and Datasets: Microsoft offers sample Power BI reports and datasets (such as the Financial sample or Retail analysis sample) which you can download and explore[4]. These can inspire you and help you see how data is structured and visuals are used in a finished report. Within Power BI Desktop, under the Help tab, there’s an option “Examples” -> “Show Examples” (or “Try a sample dataset”) which can load a built-in sample dataset for you[4].

• Books and Blogs: There are many books on Power BI and DAX (the formula language) if you prefer reading in-depth. Additionally, community experts maintain blogs with tutorials on specific topics (like Enterprise DNA, SQLBI for DAX, etc.). As you advance, these can be useful for mastering more complex aspects.

• Practice: Finally, the best way to learn is by doing. Take your own data (or use the provided sample) and try to replicate something you’ve done in Excel in Power BI. Create a few visuals, experiment with filters and slicers, and try adding a calculated measure. If you have specific analysis questions, use Power BI to answer them. With each exercise, you’ll become more comfortable and curious to learn more.

By now, you should have a solid foundation in getting data into Power BI Desktop and navigating the interface. In summary, we covered:

• The layout of Power BI Desktop (ribbon, panes, canvas)[3] and what each part is used for.
• How to use Get Data to import an Excel sales dataset[1], and how the data appears in the Fields pane.
• Creating a simple visual (column chart) by dragging fields[1].
• The purpose of Save and Publish, and how to do both[2][2].
• Best practices for organizing your data model and report (naming, relationships, etc.)[1].
• Common beginner challenges and solutions (interface tips, data types, relationships).
• Resources to continue your Power BI learning journey.

Feel free to explore further by modifying the example or trying new visuals. In the next lesson, we will delve deeper into transforming data or creating more complex visualizations (depending on your learning path). Until then, happy Power BI exploring!