Practical Challenges
Sharpen your skills with interactive exercises and daily challenges designed around real Power BI reports.
AI writes DAX. You sign off on it. DAX Solver is where analysts train the judgment that prompts can’t fake.
-- YoY revenue growth VAR CurrentYear = CALCULATE( SUM(Sales[Amount]), YEAR('Date'[Date]) = 2025 ) VAR PriorYear = CALCULATE( SUM(Sales[Amount]), DATEADD('Date'[Date], -1, YEAR) ) RETURN DIVIDE(CurrentYear - PriorYear, PriorYear)
Most languages fail loudly. DAX doesn’t. A wrong measure returns a number — not an error — and that number ends up in dashboards, board decks, and the decisions your business runs on. In the age of Copilot, where AI writes the measure and a human just pastes it, that’s how quiet bugs become loud mistakes.
-- Looks reasonable. Returns a number. AVERAGE(Sales[Amount])
-- What the business actually means. DIVIDE( SUM(Sales[Amount]), DISTINCTCOUNT(Sales[OrderID]) )
Same model. Same question. Different answers.
Copilot will happily write either. You have to know which.
Every tool here is built for one thing: the hands-on reps that turn a DAX learner into someone their team trusts to sign off on the number.
Sharpen your skills with interactive exercises and daily challenges designed around real Power BI reports.
Write, test, and optimize your DAX expressions with autocomplete, code formatting, and syntax highlighting.
Daxie nudges you toward the answer instead of handing it over — so the understanding is yours, not the model’s.
Track your DAX journey with custom analytics that highlight your strengths, areas for improvement, and overall progress.
Run DAX queries across multiple semantic models — Finance, HR, Retail, Manufacturing, and more.
Tackle challenges from real practitioners, built on real-world use cases — and share your own.
You won’t just write DAX that runs. You’ll know why it’s right.
Browse hundreds of problems across Finance, HR, Retail, and more — filtered by skill level, model, or topic.
Use our intelligent editor with autocomplete, formatting, and hover docs. Inspect the model and run your measure against the test suite.
Stuck? Ask Daxie for a hint. Keep iterating until every test case passes — and you’ve truly learned the concept.
Watch your skills grow with custom analytics — personal bests, streaks, and the areas where you’ve leveled up.
Real semantic models with role-playing dimensions, inactive relationships, and the kind of ambiguity that trips up both beginners and Copilot. Train on the shapes your org actually ships — not a toy star schema.
Six guided courses built around the AdventureWorks dataset — from fundamentals to advanced techniques. Practice real DAX against real data, one problem at a time.
Variables, measures, and your first CALCULATE. The foundation every analyst needs.
Year-over-year growth, moving averages, and custom date calculations done right.
ALL, CALCULATE, FILTER — the pattern that trips up both beginners and Copilot.
IF, IFERROR, COALESCE, ISNUMBER. Handle blanks, errors, and edge cases cleanly.
140 problems pulled from real forum questions — the gotchas the docs don’t cover.
UPPER, LOWER, LEFT, MID, REPLACE, SUBSTITUTE, FORMAT, SEARCH — string wrangling in DAX.
Most AI writes DAX for you. Daxie trains you to spot when the AI is wrong. Ask about a function, a filter-context gotcha, or why your measure returns blank — and get guidance that makes you the expert, not the chatbot.
Ask Daxie to break down CALCULATE, filter context, or any DAX concept — and get explanations that actually help you learn.
Attach your current code or the last error with one click. Daxie sees the whole picture before offering guidance.
Daxie guides you toward the answer instead of just handing it over — so you build real DAX skills along the way.
CALCULATE return blank?
VALUES('Date'[Year]) and let me know what changes.
Real posts from Power BI and DAX practitioners on Reddit. Every one of them is describing the same thing: DAX that ships wrong, models that behave unexpectedly, measures that look right but aren’t.
Most of the problems I see with customers are where Copilot is generating the correct answer to a question that is not the one the customer thought they were asking.
My favorite, the total is wrong since it’s not calculating from the individual rows… I don’t want know how many hours I tried to debug it.
Making sure data flows don’t silently corrupt something downstream, that replays don’t double count.
There is no such thing as a CORREL function in DAX and this page is a distraction in the search results.
A lot of measures are technically correct… but still perform really badly. What’s tricky is the result is still correct, so at first everything looks fine.
…a very confident-looking but slightly wrong number. And slightly wrong in OEE can mean big operational decisions.
One semantic slip (answering a different question) and you get a measure that ‘works’ but is wrong.
I tried to recreate their total and came up with a different number, they dropped it instead of having the conversation.
The hardest thing about DAX is that, depending on what you’re doing, you can’t debug the steps to see what’s going on… You’re out of luck.
We have around 20 reports all linked to the same dataset… So why on earth is this measure returning a value 55M less than it should be?
How wrong copilot can be for it’s own major product.
I should be getting 1220 but I get 1420.
Onboard new analysts on real models. Run skill audits before you stake a quarter on a project. Screen candidates against your own schema — not a generic coding quiz.
Prompts are cheap. Verification is the skill. Start building it today — free, no credit card.