Most people first open Power BI Desktop because someone sent them an Excel file or a SharePoint list and said, “Can you make this easier to understand for the team?” You might be tracking sales, tickets, projects, or headcount, but everything is stuck in rows and columns.
Power BI Desktop helps you turn that raw data into simple, interactive visuals and reports you can share with others. This tutorial walks you through that entire journey in a practical way: from installation to publishing a finished report.
What is Power BI Desktop (in simple words)
Power BI Desktop is a free Windows application from Microsoft that lets you connect to data, clean it, build a data model, and create interactive reports. You then publish those reports to the Power BI Service (Power BI online) so others can view them in a browser or on mobile.
With Power BI Desktop you can:
- Connect to Excel, CSV, SharePoint lists, databases, and many other sources.
- Clean and shape messy data using Power Query.
- Build relationships between tables and create measures using DAX.
- Design interactive reports and dashboards with charts, tables, and slicers.
- Publish reports securely to Power BI Service and share with your team.
If you think in Excel terms: Power Query = Get & Transform, Power Pivot = data model and DAX, Power View = visuals. Power BI Desktop bundles all of these into one tool.
Power BI Desktop vs Power BI Service
You’ll often hear both “Power BI Desktop” and “Power BI Service”, and it’s important to be clear about what lives where.
- Power BI Desktop:
- Installed on your Windows machine.
- Used for connecting to data, transforming it, building the model, and designing reports.
- Full Power Query and modeling capabilities.
- Power BI Service (app.powerbi.com):
- Cloud (browser-based).
- Used for sharing, scheduling refresh, workspaces, apps, permissions, and collaboration.
- Limited modeling; it assumes most modeling was done in Desktop.
A simple way to remember: build in Desktop, share and manage in Service.
Install and Open Power BI Desktop
You have two main ways to install Power BI Desktop.
- Microsoft Store (recommended):
- Open Microsoft Store on Windows and search for “Power BI Desktop”.
- Click Get/Install.
- Updates are handled automatically via the Store.
- Direct download:
- Go to the official Power BI Desktop download page.
- Choose your language and download the 64‑bit installer (most modern machines) like in the screenshot below.
- Run the installer, accept the license, pick the install folder, and finish the setup.
Once installed:
- Open Power BI Desktop from the Start menu.
- You’ll see a blank report canvas and a “Get data” option on the Home ribbon.
Now in your desktop, you can see the Power BI Desktop. In this way you can install the power bi desktop in your local computer
Power BI Desktop Interface
When Power BI Desktop opens, look at four main areas.
- Ribbon: Tabs like Home, Insert, Modeling, View. You’ll use Home a lot (Get data, Transform data, Refresh, Publish).
- Report canvas: The white area where you build your visuals and arrange them.
- Fields pane: On the right, showing tables and columns from your data.
- Visualizations pane: Also on the right, where you pick chart types and configure fields (Axis, Values, Legend, Filters, etc.).
On the left side, you’ll also see three small icons:
- Report view (canvas with visuals).
- Data view (table icon, to see raw rows after loading).
- Model view (relationships diagram between tables).
You’ll switch between these often as you build reports.
Step 1: Connect to Your Data (Get Data)
The first thing you do in almost every project is connect to data.
From the Home tab:
- Click Get data from the ribbon.
- You’ll see common sources: Excel, Power BI datasets, SQL Server, Web, Text/CSV, SharePoint Online list, etc.
Some common everyday use cases:
- Excel: Local or network Excel files (sales.xlsx, budget.xlsx, etc.).
- CSV: Export from another system (CRM, ticketing tool, HR system).
- SharePoint Online list: Task lists, issue trackers, project lists.
- SQL Server / other databases: Central data warehouse or app database.
Example: Connect to an Excel file
- Home → Get data → Excel.
- Browse to your file and click Open.
- Navigator window shows available sheets/tables; tick the ones you want.
- Click Transform data if you want to clean it first, or Load if it’s already clean. You can see it in the screenshot below:
Step 2: Clean and Transform Data in Power Query
Power Query is where you fix problems like extra columns, wrong data types, and inconsistent values.
Some common tasks you’ll do in Power Query:
- Remove unwanted columns (Remove Columns).
- Filter out blank or error rows.
- Change data types (e.g., text to date or whole number).
- Split columns (e.g., “Full Name” into First Name and Last Name).
- Merge or append queries (combine tables).
Basic flow:
- In Navigator, click Transform data.
- Power Query Editor opens with a preview of your data.
- Use the Home and Transform ribbons for most operations.
- Every step you apply shows up in the Applied Steps pane on the right.
- When done, click Close & Apply to send the cleaned data back to Power BI Desktop.
Good practice:
- Rename your queries to meaningful names (e.g., “Sales”, “Products”, “Calendar”).
- Avoid doing heavy data cleaning in Excel; centralize it in Power Query so it’s repeatable on refresh.
Step 3: Build a Data Model and Relationships
Once data is loaded, Power BI creates a data model behind the scenes. If you only have one table, you can start building visuals right away. If you have multiple tables (Sales, Products, Customers, Dates), you should define relationships so visuals work correctly.
To see relationships:
- Click the Model view icon on the left (diagram icon).
- You’ll see tables as boxes and lines between them representing relationships.
Typical pattern (star schema):
- One central fact table (e.g., Sales, Orders, Tickets).
- Several dimension tables (e.g., Date, Product, Customer, Region).
- One‑to‑many relationships from each dimension to the fact table.
To create or edit a relationship:
- Drag a field from one table onto the matching field in another (e.g., ProductID to ProductID).
- Or, Home → Manage relationships → New.
- Set:
- Table and column (from and to).
- Cardinality: Many to one (most common).
- Cross-filter direction: Single or Both (use Both only when you know why).
A clean model with correct relationships makes your visuals behave properly when users slice by date, product, or region.
Step 4: Create Your First Visuals
Now the fun part: turning the model into charts and tables on the report canvas.
Basic steps to create a visual:
- Go to Report view (left side).
- In the Visualizations pane, pick a visual type (e.g., Clustered column chart, Table, Card, Line chart).
- Click on the canvas to place it.
- Drag fields from the Fields pane into the appropriate wells (Axis, Values, Legend, etc.). Here is a screenshot for your reference.
Example: Sales by Month column chart
- Select Clustered column chart.
- Drag Date (Month) to Axis.
- Drag Sales Amount to Values.
- Format the chart using the Format pane (title, colors, data labels).
Useful visual types to start with:
- Table: For detailed data, similar to Excel.
- Matrix: Like a pivot table (rows, columns, values).
- Card: Shows a single big number (total sales, total tickets, etc.).
- Column/bar charts: Compare values across categories.
- Line charts: Show trends over time.
Keep visuals simple. Aim for each visual to answer one clear question (“How are sales trending?”, “Which region is highest?”, etc.).
Step 5: Add Slicers and Filters for Interactivity
Slicers and filters make your report interactive so users can explore data on their own.
To add a slicer:
- Choose the Slicer visual.
- Drag a field like Region, Product Category, or Year to the Field well.
- Resize and position it on the canvas.
Users can now click values in the slicer to filter all visuals on the page.
Other filter options:
- Visual‑level filters: Only affect one visual (configured in the Filters pane).
- Page‑level filters: Affect all visuals on that page.
- Report‑level filters: Affect all pages in the report.
A simple design pattern:
- Put a few key slicers (Date, Region, Category) on the left or top of the page.
- Use the Filters pane only for things users don’t need to see (e.g., filter out test data).
Step 6: Create Simple Measures with DAX
You can do a lot with out‑of‑the‑box aggregations (sum, average, count), but DAX measures give you more control. Measures are calculations that react to the filters on the report (slicers, cross‑highlighting, etc.).
To create a measure:
- Go to the Modeling tab.
- Click New measure.
- Type a DAX formula, for example:
- Total Sales = SUM(Sales[SalesAmount])
- Distinct Customers = DISTINCTCOUNT(Sales[CustomerID])
- Press Enter. The measure appears in your Fields pane with a calculator icon.
Use cases for measures:
- Ratios and percentages (e.g., % of total, conversion rate).
- Year‑to‑date, month‑to‑date calculations.
- Comparisons vs last year or vs target.
You don’t have to master DAX on day one. Start with simple sums and counts, then gradually move into time intelligence and more advanced logic as your reports mature.
Step 7: Format and Layout Your Report
A little formatting makes your report much easier to read.
Things worth doing:
- Rename visuals and fields to user‑friendly names (no technical jargon).
- Add clear titles to each visual (“Sales by Region”, “Tickets by Status”).
- Turn on data labels where it helps (but avoid clutter).
- Use consistent colors for the same category across visuals.
- Use themes (View → Themes) to quickly standardize colors and fonts.
For a darker look, you can pick a darker built‑in theme from View → Themes, such as Innovate, which gives a dark canvas feel even though there isn’t a full Desktop “dark mode” feature for the app itself.
Try to keep each report page focused on one main story:
- Page 1: Overview (KPIs and high‑level charts).
- Page 2: Details by product.
- Page 3: Details by region or customer.
Step 8: Publish to Power BI Service and Share
Once you’re happy with your Power BI report, you’ll usually want to share it with others.
To publish:
- Save your .pbix file.
- In Power BI Desktop, go to Home → Publish (or File → Publish → Publish to Power BI).
- Sign in with your Power BI account if prompted.
- Choose a workspace (e.g., My workspace or a shared workspace) and click Select.
After publishing:
- Go to app.powerbi.com in a browser.
- Open the workspace you published to.
- You’ll see both the report and a dataset (semantic model) with the same name.
From there you can:
- Share the report with colleagues (they need the right Power BI license and permissions).
- Pin key visuals as tiles to a dashboard.
- Set up scheduled refresh if your data source supports it (so the report stays up to date).
Power BI Desktop and SharePoint
Since you work with SharePoint a lot, it’s worth calling out how nicely it works with Power BI.
Common patterns:
- Connect directly to a SharePoint Online list from Power BI Desktop (Get data → More → Online Services → SharePoint Online List).
- Connect to Excel files stored in SharePoint or OneDrive (using the file’s URL or via SharePoint folder connector).
- Build your report in Desktop, publish to Power BI Service, and then embed that report in a SharePoint Online page using the Power BI web part.
This is a powerful combo: SharePoint stores and manages the data and pages, while Power BI provides the visual reporting layer your users see.
Best Practices
Here are a few best practices that will help in real projects:
- Start small: Don’t try to build a “perfect” enterprise model on day one. Start with a single use case (e.g., monthly sales report) and iterate.
- Name things clearly: Table names, column names, measures, and pages should all be understandable to business users.
- Avoid too many visuals on one page: A few good charts beat a crowded page where nothing stands out.
- Use a Date table: For anything time‑based, create or import a proper Date table and mark it as a Date table (Modeling → Mark as date table). This makes time intelligence functions work correctly.
- Document refresh: Note how the data is refreshed (manual, gateway, schedule) so the team knows how “fresh” the numbers are.
If you’ve followed this tutorial, you now know the full journey in Power BI Desktop – from connecting your data, cleaning it in Power Query, and building a solid data model, to designing clear visuals and publishing your report.
You don’t need to be a BI expert to get value out of it; even simple reports can save your team hours of manual Excel work and give them answers in a few clicks. Start with one small use case, keep your model and visuals clean, and then iterate as questions come up – that’s how most real‑world Power BI solutions grow over time.
You may also like the following tutorials:
- Create Ribbon Chart in Power BI
- Power BI Table Visual
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- Add and Customize Button Slicer in Power BI
After working for more than 18 years in Microsoft technologies like SharePoint, Microsoft 365, and Power Platform (Power Apps, Power Automate, and Power BI), I thought will share my SharePoint expertise knowledge with the world. Our audiences are from the United States, Canada, the United Kingdom, Australia, New Zealand, etc. For my expertise knowledge and SharePoint tutorials, Microsoft has been awarded a Microsoft SharePoint MVP (12 times). I have also worked in companies like HP, TCS, KPIT, etc.
