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Level 1 · Entry Foundations

Goal: go from a raw CSV file to a clean, published, filterable sales dashboard — and understand each step well enough that you could explain why the numbers are right.

Most beginner material treats Power BI as a charting tool. This level treats it as a pipeline with three stages you will keep returning to for the rest of the course:

  1. Get and transform — Power Query pulls data from a source and applies a recorded list of cleaning steps.
  2. Model — the cleaned tables are loaded into an in-memory model where you add relationships and DAX measures.
  3. Visualize and share — report pages query the model; the service publishes, refreshes and shares them.

A mistake at stage 1 (a number stored as text, a date parsed in the wrong locale) shows up as a wrong total at stage 3, so the early lessons are deliberately careful about types and cleaning.

Modules

  1. What Power BI Is: Desktop, Service & Mobile — the pieces of the platform, what each is for, and how licensing works in general terms
  2. Getting Data — connectors, CSV and Excel imports, the Navigator, and Import vs DirectQuery at a first glance
  3. Power Query Basics — the editor, applied steps, and the M code each click writes
  4. Data Types & Cleaning — types, locales, trimming, splitting, replacing errors, and unpivoting
  5. Building Your First Visuals — choosing a visual, field wells, implicit aggregation, and the model query behind each chart
  6. Filters & Slicers — visual, page and report filters, slicers, and cross-filtering between visuals
  7. Measures vs Calculated Columns — the most important distinction in Power BI, with worked examples
  8. Report Formatting & Layout — canvas settings, themes, number formats, alignment, and a layout grid
  9. Publishing & Sharing Basics — workspaces, publishing, reports vs semantic models vs dashboards, and sharing options
  10. Project — A Sales Dashboard from CSV — build, verify and publish a one-page dashboard from a sample file defined in the lesson

What you need before starting

  • A Windows PC (or Windows virtual machine) for Power BI Desktop, which is a free download from Microsoft. Desktop does not run natively on macOS or Linux.
  • A work or school Microsoft account if you want to publish to the Power BI service. Personal consumer email addresses generally cannot sign up for the service; lesson 09 explains the options.
  • Comfort with spreadsheets: sorting, filtering, and SUM/AVERAGE-style formulas.

The sample data used in this level

Most lessons use one small file, trailhead_sales.csv, for an imaginary outdoor-gear shop. It is short enough to check every total by hand:

OrderID,OrderDate,Region,Product,Category,Units,UnitPrice
1001,2025-01-05,North,Trail Tent,Camping,2,120.00
1002,2025-01-09,South,Rain Jacket,Apparel,3,80.00
1003,2025-01-17,North,Headlamp,Accessories,5,25.00
1004,2025-02-02,East,Trail Tent,Camping,1,120.00
1005,2025-02-14,South,Headlamp,Accessories,4,25.00
1006,2025-02-20,East,Rain Jacket,Apparel,2,80.00
1007,2025-03-03,North,Rain Jacket,Apparel,1,80.00
1008,2025-03-11,South,Trail Tent,Camping,3,120.00

Save it as a UTF-8 text file. Revenue (Units × UnitPrice) per row is 240, 240, 125, 120, 100, 160, 80 and 360, for a grand total of 1,425. You will see that number many times; if your report shows something else, something upstream is wrong.