Power BI is Microsoft's tool for turning business data into dashboards that update by themselves. We teach it in Week 8 of our Data Science and Machine Learning course. It gets a full week, from cleaning data in Power Query to writing DAX formulas and publishing a finished report. By then you already know Python, SQL and statistics, so you are not learning data and Power BI at the same time.
What Power BI is, and why it matters
A manager does not want a notebook full of code. They want one page that shows sales, costs and trends, and lets them click a branch or a month to filter it. Power BI builds that page. It connects to Excel files, databases and other sources, cleans the data, and keeps the report fresh on a schedule.
Power BI has two main parts:
- Power BI Desktop: the app where you build reports. Microsoft offers it as a free download, and it runs on Windows.
- Power BI Service: the online side, where you publish reports so other people can open them.
Dashboards are a big part of data analyst work, which is why we give Power BI a full week instead of a single class.
What you learn in the Power BI week
Power Query: cleaning the data
- Profiling data to see what is missing or wrong
- Fixing types, pivoting and unpivoting columns
- Merge versus append, the two ways to combine tables
- Splitting data into fact tables (the events, such as sales) and dimension tables (the details, such as products or dates)
Data modelling
- The star schema: one fact table in the middle, dimension tables around it
- Relationships between tables and which way filters flow
- A proper Date table, so time comparisons work
DAX: the formulas behind every number
DAX is Power BI's formula language. Before writing any, you write a plain-English definition of the metric, such as exactly who counts as an active user. Then you learn:
- Measures versus calculated columns, and when to use each
- CALCULATE, the function most Power BI work depends on, with ALL and ALLEXCEPT
- SUMX and VAR/RETURN for cleaner formulas
- Time intelligence: year-to-date totals with TOTALYTD and last-year comparisons with SAMEPERIODLASTYEAR
Report design and publishing
- Slicers, drillthrough, bookmarks and tooltips
- Layouts for phones and for readers with accessibility needs
- Publishing to the Power BI Service with scheduled refresh
- Row-Level Security, so each person sees only their own rows
- Copilot in Power BI to draft measures, with every one read and corrected by you
Some topics are covered as awareness only, so you know they exist and can read about them later. These include DirectQuery, dynamic Row-Level Security, calculation groups and paginated reports.
The weeks that lead up to it
The Power BI week works because of what comes first. In Week 3 you do pivot tables and XLOOKUP in Excel, then the same in pandas. In Week 4 you learn SQL. In Week 7 you build Streamlit dashboards and get a short primer on filter context, the idea that a slicer changes what a number adds up. You also compare when to choose Power BI and when to choose Streamlit.
What you build and practise
The week ends with one published end-to-end report: data cleaned in Power Query, a star-schema model, DAX measures and a designed report page. You also get a one-to-one with your mentor to choose your final project. One option in the project pool is a banking or fintech Power BI dashboard with SQL, Power Query, DAX and Row-Level Security.
If you are not sure whether to start with Excel or Power BI, read our comparison: Power BI or Excel, which to learn first.
Who this suits
- People in finance, operations or marketing who already build reports in Excel
- Beginners who want a data analyst or Power BI analyst role
- Managers who want to read and question dashboards with confidence
You need a laptop with at least 8GB of RAM. Since Power BI Desktop runs on Windows, ask us before joining if you use a Mac.
Taught inside the full course
Power BI is one week of the 12-week Data Science and Machine Learning course, not a standalone class. Around it you learn Python, SQL, statistics and starter machine learning. Classes run Monday to Friday, 2 hours a day, in Old Baneshwor, with at most 10 students. You can also join from outside Kathmandu on a live online seat.
Common questions
Can I join only for the Power BI week?
No. Power BI is Week 8 of the Data Science and Machine Learning course. It builds on the Excel, SQL and dashboard work from the earlier weeks.
Is DAX covered in depth?
Yes. You practise CALCULATE, ALL, ALLEXCEPT, SUMX, VAR/RETURN and time intelligence until you can use them confidently. Calculation groups and RANKX are covered as awareness.
Do I need to know Excel first?
Basic computer use is enough. The course covers pivot tables and XLOOKUP in Week 3, well before Power BI.
Will I publish a real report?
Yes. The week ends with one published end-to-end report, with data cleaned in Power Query, a modelled dataset and DAX measures.