Learn
A plain definition of each tool, when to use it, where it breaks, and a short video. Click any dotted word for an explanation in everyday language.
DATA ANALYTICS, WITHOUT THE JARGON
Six tools. One path. Stop guessing which to open.
Most people learn Excel, then hear about Power Query, Power Pivot, DAX, and Power BI and assume they are rival products competing for the same job. They are not. They are steps. Each one exists because the step before it ran out of room — the file got too big, the cleanup got too repetitive, or somebody else needed to see the result. This studio teaches you to recognize which wall you just hit, and which tool is waiting on the other side of it.
Free. Sign up with your email and a password, or use Google. Files you analyze stay on your own machine.
quick & by handmodeled · refreshable · shared
XLExcelSmall files you can look at
PTPivot TablesOne clean table only
PQPower QueryRepeat the same cleanup each period
P²Power PivotMany tables, millions of rows
fxDAXMeasures and time comparisons
BIPower BIDashboards you publish and protect
And when the whole stack runs out of room — past a million rows, a statistic DAX cannot express, a script you need to version-control — Python and R are covered as backups, with honest advice about when reaching for them is overkill.
Every tool also has a character, because “Marge the Mashup Machine washes your files” sticks in your head better than “Power Query is an ETL layer.” Cell-by-cell Carl does everything by hand. Captain Totals adds up one clean table and nothing more. Relatable Rhonda links tables so you can stop writing VLOOKUPs. Meet all eight inside — or ignore them entirely and read the plain reference instead. Both versions cover the same material.
What you can do once you are in
Play
The same six tools with faces. A cartoon map, a cast of characters, and three quick games — match the problem to the tool, put the path in order, and pick who to call.
Decide
Five questions about your file — how big, how messy, how many sources — and you land on one tool, with the reasoning spelled out.
Analyze
Drop in a CSV or Excel file and get row counts, column types, cleanup flags, and charts. The file is read inside your browser and never uploaded.
Ask
Describe the task in your own words and get a recommendation you can argue with. It can use the file you just profiled.
Your data stays yours
When you upload a spreadsheet to Analyze, it is read and profiled by your own browser. The file itself is never sent to a server and never stored. Only a non-identifying summary — how many rows, which column types, which tool was suggested — is recorded, so usage trends can be reviewed later.
Ready to stop guessing?
Create an account and start on the plain reference. It takes a minute.