A hands-on, project-based 2-day course for learning Microsoft Power BI Desktop. Students build real dashboards from raw data using local CSV files (Day 1) and a cloud Snowflake database (Day 2).
Note: This course uses Power BI Desktop throughout. A Microsoft 365 or Power BI Pro account is not required.
This course teaches Power BI as a tool — but the real goal is to develop analytical thinking. Knowing how to click through a BI tool is a commodity skill. Knowing what to build, why to build it, and which visualization best communicates your insight — that's what makes an analyst valuable.
What we believe:
- The question always comes before the chart. A dashboard built without a business question is just decoration.
- Chart choice is not a matter of preference — different relationships in data require different visual encodings. Using the wrong chart obscures insight.
- Every number needs a comparison. Raw totals mean nothing without a benchmark, a trend, or a target.
- Data storytelling is a skill. The best analysts don't just find insights — they communicate them so clearly that action follows.
Where Power BI fits in the analytics landscape: Power BI is primarily a tool for descriptive and diagnostic analytics — answering "what happened?" and "why did it happen?" These two types cover the vast majority of real-world business analytics needs. Understanding where the tool fits helps you know both what it's excellent at and where its limits are.
📖 Before starting Day 1, read
Analytics Foundations.md— it covers the 4 types of analytics, the Visual Vocabulary framework for choosing charts, and the principles of data storytelling. These concepts will inform every design decision you make during the course.
| Activity | File | Description |
|---|---|---|
| Main guide | Day 1/Power BI Desktop Day 1.md |
Full step-by-step instructions |
| Datasets | Day 1/datasets/ |
6 CSV files (NY property, e-commerce 2017–2019, products, stores) |
| Challenge mockup | Day 1/challenge-mockup.html |
Target dashboard for the end-of-day challenge |
| Solution | Day 1/solution/ |
Reference .pbix file |
What students build:
- Part 1: NY Property Sales — first visuals, basic interactions
- Part 2: E-Commerce Sales Dashboard — Power Query cleaning, Append Queries (combining 3 years of data), star schema relationships, slicers, drill hierarchy
- End-of-day Challenge: Build a Sales Summary page independently from a mockup
Key skills covered: CSV import, Power Query transformations, Append Queries, data types, table relationships, column/bar/line charts, slicers, cross-filtering
Work through the files in this order:
| # | Activity | File | Est. Time |
|---|---|---|---|
| 1 | Connect to Snowflake | Day 2/Connecting to Snowflake.md |
60–75 min |
| 2 | DAX Fundamentals | Day 2/DAX Fundamentals Lab.md |
25–30 min |
| 3 | Time Intelligence | Day 2/Time Intelligence Lab.md |
25–30 min |
| 4 | Challenge | Day 2/challenge/Challenge Brief.md |
45–60 min |
| 5 | Advanced Features | Day 2/Advanced Features Lab.md |
20–25 min |
Challenge resources (in Day 2/challenge/):
| File | Purpose |
|---|---|
Challenge Brief.md |
Requirements — what to build and success criteria |
mockup.html |
Visual target — open in browser |
hints.md |
Step-by-step guidance with checkpoints (use only if stuck) |
Key skills covered: Snowflake connection, Import vs DirectQuery, star schema (7 tables), DAX measures vs. calculated columns, CALCULATE, filter context, DIVIDE, Date table, TOTALYTD, SAMEPERIODLASTYEAR, drill-through pages, bookmarks, Q&A natural language visual
- Power BI Desktop installed (free — download here)
- Snowflake account with access to
CHINOOK_DB(Day 2 only — provided by instructor) - No prior Power BI experience required
- Basic comfort with spreadsheets is helpful
| Dataset | Location | Used in |
|---|---|---|
ny_property_sales.csv |
Day 1/datasets/ |
Day 1 Part 1 |
sales2017_raw.csv |
Day 1/datasets/ |
Day 1 Part 2 (messy data exercise) |
sales2018.csv |
Day 1/datasets/ |
Day 1 Part 2 (Append Queries) |
sales2019.csv |
Day 1/datasets/ |
Day 1 Part 2 (Append Queries) |
producthierarchy.csv |
Day 1/datasets/ |
Day 1 Part 2 (product dimension) |
store_cities.csv |
Day 1/datasets/ |
Day 1 Part 2 (store/geography dimension) |
| Chinook DB (Snowflake) | Cloud | Day 2 (all activities) |
By the end of this 2-day course, students will be able to:
- Import and clean data from CSV files and cloud databases
- Build star schema data models with proper relationships
- Use Power Query to transform, append, and reshape data
- Write DAX measures and calculated columns
- Apply time intelligence (YTD, year-over-year comparisons)
- Create professional reports: cards, charts, maps, tables, treemaps
- Add interactivity: slicers, cross-filtering, drill-through, bookmarks
- Use the Q&A natural language feature for exploratory analysis
Analytics Foundations.md— Start here. The 4 types of analytics, visual vocabulary, chart selection, and data storytelling principlesDAX-Guide.md— Comprehensive DAX reference with Chinook examplesWorking With Power BI-Outline.pdf— Original course outlineWorking with PowerBI Slides.pdf— Slide deck (storytelling, analytics types, BI importance)- Tableau Visual Vocabulary — The definitive reference for choosing the right chart type
- Power BI Desktop Documentation
- DAX Reference
- From Data to Viz — Interactive decision tree for chart selection
- Power BI Community
For questions or feedback, contact the instructor.