What Is Power BI Desktop vs Service vs Mobile? A Beginner's Tour of Views, Visuals and Saving a .pbix File

By Ravindra Bagale · Last updated: 16 October 2026

Practice files: blinkit-orders-tour.csv (6 orders for the tour) and blinkit-store-cities.csv (4 stores, a lookup table).

Made-up data: fictional Blinkit-style orders from Maharashtra cities, for practice only. Amounts are in ₹ and dates are DD-MM-YYYY.

1. The problem

A store manager in Pune wants to see this year's sales on her phone every morning. The data sits in CSV exports and a database. Where do you build the report, how does it reach her phone, and what do you need to install? Beginners often open Power BI, see three panes and four icons, and do not know where to start. A clear map saves hours.

2. The idea in simple words

Build on Desktop › publish to the Service › view on Mobile. Signing in to the Service needs a work or school email (an organisation account), not a personal Gmail address.

Excel or Power BI? Excel is good at storing and calculating data in sheets. Power BI is built for analysing and presenting it. When you import data, Power BI also keeps a compressed copy in its own model inside the .pbix, which is why it handles far more rows than a worksheet.

3. The data

Where data comes from (Get data › More shows hundreds of connectors):

How big is big? 1 KB = 1,024 bytes, 1 MB = 1,024 KB, 1 GB = 1,024 MB, 1 TB = 1,024 GB, then PB and EB. Roughly: text and CSV files for small data, Excel up to about a million rows per sheet, databases for gigabytes to terabytes, data lakes and warehouses for petabytes.

The tour file blinkit-orders-tour.csv:

Total revenue ₹2,979, units 11. By city: Nashik 1,350, Pune 1,239, Nagpur 270, Kolhapur 120.

4. Step by step

Load the file

1. Open Power BI Desktop. Home › Get data › Text/CSV › blinkit-orders-tour.csv › Load. (For messy files you click Transform Data instead; the next chapters show how.)

The three views (icons on the left)

2. Report view (the bar-chart icon): the canvas where you build visuals. Pages are the tabs at the bottom.
3. Table view (the grid icon): the loaded rows. Select the table in the Data pane and read the row count at the bottom: 6 rows. You may see store_id as 101 instead of 0101: Power BI guessed that it is a number and dropped the leading zero. The next chapter shows why IDs should stay text.
4. Model view (the three-boxes icon): tables and the relationships between them. With one table there is one box.

Build a visual

5. Back in Report view, click Clustered column chart in the Visualizations pane (Build visual). Drag city to the X-axis and revenue to the Y-axis. You get 4 bars: Nashik 1,350, Pune 1,239, Nagpur 270, Kolhapur 120.
6. Click the paintbrush (Format visual) to change how it looks: turn on Data labels, change colours, set a title. The Build tab decides what is shown; the Format tab decides how it looks.
7. Click empty canvas, then Card in the Visualizations pane and drag revenue onto it: 2,979 (or 2.98K until you set Display units to None).

Add a lookup table

8. Get data › Text/CSV › blinkit-store-cities.csv › Load. Model view now shows two boxes, blinkit-orders-tour and blinkit-store-cities.

Save

9. File › Save as › Browse this device › choose a folder such as Downloads › name it blinkit-tour › Save. The file is blinkit-tour.pbix.

5. Your result should look like this

• Report view: a column chart with 4 city bars and a card showing 2,979.
• Table view: 6 rows of orders; the store table shows 4 rows.
• Model view: 2 tables.
• In your folder: blinkit-tour.pbix. Close Power BI and open the file again: the chart, the card and both tables are still there.

6. What happened

• Load imported both CSV files into the model stored inside the .pbix, so the report works even if the CSV is moved, until you refresh.
• The column chart grouped the 6 orders by city and summed revenue. Pune has two orders (240 + 999 = 1,239), Nashik two (450 + 900 = 1,350).
• Saving wrote the queries, the model, the data and the report pages into one .pbix file.

7. Explore further

• The project you will build. The next chapters follow one sales project: yearly order files (2023, 2024, 2025), a store_cities table (store_id › city) and a product table (product › category › sub-category). The plan:
  • Append stacks the yearly files into one sales table: see How to Append Multiple Years of Sales Data in Power BI Power Query.
  • Merge joins the lookup tables onto sales by a common column: see How to Merge Tables in Power BI Power Query (Left Outer vs Inner Join).
• Visual types to know first: bar and column (compare items), line and area (trends over time), map (places), pie and donut (parts of a whole, few items), matrix (rows × columns), card (one number).
• Power BI Desktop runs only on Windows. On a Mac, use a Windows PC or a Windows virtual machine; the Service works in any browser.
• Save often. Ctrl+S after every few steps. Power BI does keep auto-recovery files, but do not rely on them.

8. Common mistakes

9. Practise on your own

10. Think like a professional

• Business view. Decide who looks at the report and on which device before you build. A report meant for phones needs fewer, larger visuals.
• One file, one subject. Keep a sales report in one .pbix; do not mix unrelated projects.
• Know your source. Files are fine to learn with; real projects usually read from a database, so you will need its server address and an account.
• Name things. Rename tables and pages (sales, store_cities, Overview) as soon as you create them.

Interview questions

1. What is the difference between Power BI Desktop, Service and Mobile? Desktop builds reports, the Service publishes and shares them, Mobile views them.
2. What are the three views in Power BI Desktop? Report, Table (Data) and Model.
3. Does Power BI store data? Yes, imported data is stored compressed in the model inside the .pbix.
4. Append vs Merge? Append stacks rows of similar tables; Merge adds columns from another table using a common column.

Recap

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