Power BI Cheat Sheet

Workflow: Get data → clean it in Power Query → build the model (relationships + DAX measures) → design report visuals → publish to the Power BI Service.

48 entries
7 sections
Updated 1 Oct 2026

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48 entries

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Desktop Shortcuts #

Shortcut	Action
`Ctrl + S`	Save
`Ctrl + Z` / `Ctrl + Y`	Undo / redo
`Ctrl + C` / `Ctrl + V`	Copy / paste visuals (also between pages and files)
`Ctrl + G`	Group selected visuals
`Ctrl + click`	Select several data points / use buttons while editing
`Ctrl + /` (DAX editor)	Comment / uncomment
`Shift + Enter` (DAX editor)	New line
`Alt + ↑/↓` (DAX editor)	Move a line

Power Query (Transform data) #

Task	How
Open	Home → Transform data
Use first row as headers	Home → Use First Row as Headers
Set data types	Click the icon in the column header
Remove columns	Select the ones to keep → Remove Other Columns
Split a column	Split Column → By Delimiter
Unpivot (wide → long)	Select the ID columns → Unpivot Other Columns
Fill down empty cells	Transform → Fill → Down
Replace values / errors	Right-click the column
Join tables	Home → Merge Queries
Stack tables	Home → Append Queries
Group & summarize	Transform → Group By
Combine all files in a folder	Get data → Folder → Combine
See the M code	View → Advanced Editor

Every step appears in Applied Steps. Click a step to see the data at that point, or delete it to undo.

DAX Essentials #

Function	Example
`SUM`, `AVERAGE`, `MIN`, `MAX`	`Total Sales = SUM(Sales[Amount])`
`COUNTROWS`	`Orders = COUNTROWS(Sales)`
`DISTINCTCOUNT`	`Customers = DISTINCTCOUNT(Sales[CustomerID])`
`DIVIDE`	`Margin % = DIVIDE([Profit], [Total Sales])` (safe for 0)
`CALCULATE`	`Antwerp Sales = CALCULATE([Total Sales], Store[City] = "Antwerp")`
`ALL` / `REMOVEFILTERS`	`% of Total = DIVIDE([Total Sales], CALCULATE([Total Sales], ALL(Product)))`
`FILTER`	`CALCULATE([Total Sales], FILTER(Sales, Sales[Qty] > 10))`
`SUMX` (iterator)	`Revenue = SUMX(Sales, Sales[Qty] * Sales[Price])`
`RELATED`	`Sales[Category] = RELATED(Product[Category])` (calculated column)
`IF` / `SWITCH`	`SWITCH(TRUE(), [Sales] > 1000, "High", [Sales] > 500, "Mid", "Low")`
`SELECTEDVALUE`	`SELECTEDVALUE(Product[Name], "Multiple")`
`RANKX`	`RANKX(ALL(Product[Name]), [Total Sales])`
`VAR` / `RETURN`	Store intermediate results (see below)

Time Intelligence (needs a date table) #

Function	Example
`TOTALYTD`	`Sales YTD = TOTALYTD([Total Sales], 'Date'[Date])`
`SAMEPERIODLASTYEAR`	`Sales LY = CALCULATE([Total Sales], SAMEPERIODLASTYEAR('Date'[Date]))`
`DATEADD`	`CALCULATE([Total Sales], DATEADD('Date'[Date], -1, MONTH))`
`CALENDAR`	`Date = CALENDAR(DATE(2024,1,1), DATE(2026,12,31))`

Sales Growth % =
VAR Current = [Total Sales]
VAR LastYear = CALCULATE([Total Sales], SAMEPERIODLASTYEAR('Date'[Date]))
RETURN DIVIDE(Current - LastYear, LastYear)

Modelling Rules of Thumb #

Rule	Why
Use a star schema: fact table in the middle, dimension tables around it	Fast and simple DAX
Prefer measures over calculated columns	Calculated at query time, no extra storage
Create a dedicated date table and Mark as date table	Time intelligence works correctly
Relationships: one-to-many, single direction	Avoids ambiguous filters
Hide ID columns from the report view	Cleaner field list

Task	Where
Publish	Home → Publish
Scheduled refresh	Service → Dataset settings (on-premises data needs a gateway)
Row-level security	Modeling → Manage roles
Share / apps	Workspace → Share or Create app (needs Pro or Premium)
Export to Excel / PowerPoint	Report → Export

Tips #

Name measures clearly and keep them in a separate empty "_Measures" table.
Use the Performance Analyzer (View tab) to find slow visuals.