dax-mastery

DAX (Data Analysis Expressions) Mastery

Overview

Complete DAX reference covering evaluation contexts, CALCULATE, time intelligence, iterators, table functions, performance optimization, and advanced patterns. DAX is the formula language for Power BI measures, calculated columns, calculated tables, and RLS filters.

Evaluation Contexts

Row Context

• Created by: Calculated columns, iterators (SUMX, FILTER, AVERAGEX, etc.), row-by-row evaluation
• Each row in the table has its own row context
• Access columns directly: Sales[Amount]
• Nested iterators create nested row contexts

Filter Context

• Created by: Slicers, visual filters, page filters, report filters, CALCULATE arguments
• Determines which rows are visible to aggregation functions
• Does NOT provide row-level access (cannot use Sales[Amount] directly in a measure without aggregation)

Context Transition

• CALCULATE converts row context into filter context
• Happens when a measure is referenced inside an iterator
• Each row's column values become filter arguments

// Context transition example:
Sales Amount = SUM(Sales[Amount])

// Inside SUMX, each row triggers context transition:
Weighted Amount =
SUMX(
    Products,
    Products[Weight] * [Sales Amount]  // [Sales Amount] triggers CALCULATE internally
)

CALCULATE - The Most Important Function

CALCULATE(<expression>, <filter1>, <filter2>, ...)

Filter argument types:

Type	Example	Behavior
Boolean (table filter)	Products[Color] = "Red"	Adds filter, keeps existing context
Table expression	FILTER(ALL(Products), Products[Price] > 100)	Replaces filter on affected columns
REMOVEFILTERS	REMOVEFILTERS(Products[Color])	Removes existing filter on column
ALL	ALL(Products)	Removes all filters on table
KEEPFILTERS	KEEPFILTERS(Products[Color] = "Red")	Intersects with existing filter
USERELATIONSHIP	USERELATIONSHIP(Sales[ShipDate], Date[Date])	Activates inactive relationship
CROSSFILTER	CROSSFILTER(Sales[ProductID], Products[ID], Both)	Changes cross-filter direction

Critical rules:

• Boolean filters are syntactic sugar for FILTER(ALL(column), condition)
• Boolean filters REPLACE the existing filter on that column
• Use KEEPFILTERS to ADD to (intersect with) existing filters
• CALCULATE modifiers (ALL, REMOVEFILTERS) execute BEFORE filter arguments

Time Intelligence Quick Reference

Prerequisite: A proper Date table marked as a date table with a continuous date column.

Function	Purpose	Example
TOTALYTD	Year-to-date	TOTALYTD([Sales], Date[Date])
TOTALMTD	Month-to-date	TOTALMTD([Sales], Date[Date])
TOTALQTD	Quarter-to-date	TOTALQTD([Sales], Date[Date])
SAMEPERIODLASTYEAR	Same period, prior year	CALCULATE([Sales], SAMEPERIODLASTYEAR(Date[Date]))
DATEADD	Shift by interval	CALCULATE([Sales], DATEADD(Date[Date], -1, MONTH))
PARALLELPERIOD	Entire shifted period	CALCULATE([Sales], PARALLELPERIOD(Date[Date], -1, QUARTER))
DATESYTD	Date table filtered to YTD	CALCULATE([Sales], DATESYTD(Date[Date]))
DATESBETWEEN	Date range	CALCULATE([Sales], DATESBETWEEN(Date[Date], start, end))
PREVIOUSMONTH	Entire previous month	CALCULATE([Sales], PREVIOUSMONTH(Date[Date]))
PREVIOUSYEAR	Entire previous year	CALCULATE([Sales], PREVIOUSYEAR(Date[Date]))

Common time intelligence patterns:

// Year-over-Year Growth %
YoY Growth % =
VAR CurrentSales = [Total Sales]
VAR PriorYearSales = CALCULATE([Total Sales], SAMEPERIODLASTYEAR(Date[Date]))
RETURN
    DIVIDE(CurrentSales - PriorYearSales, PriorYearSales)

// Rolling 12-Month Total
Rolling 12M =
CALCULATE(
    [Total Sales],
    DATESINPERIOD(Date[Date], MAX(Date[Date]), -12, MONTH)
)

// Moving Average (3 months)
3M Moving Avg =
AVERAGEX(
    DATESINPERIOD(Date[Date], MAX(Date[Date]), -3, MONTH),
    CALCULATE([Total Sales])
)

Variables (VAR/RETURN)

Always use variables for readability and performance:

Profit Margin % =
VAR TotalRevenue = SUM(Sales[Revenue])
VAR TotalCost = SUM(Sales[Cost])
VAR Profit = TotalRevenue - TotalCost
RETURN
    DIVIDE(Profit, TotalRevenue)

Rules:

• Variables are evaluated once (performance benefit when reused)
• Variables capture filter context at the point of definition
• Variables can hold scalar values or tables
• Use meaningful names (not x, temp)

Iterator Functions

Iterators scan a table row by row, creating row context:

Function	Purpose
SUMX	Sum of expression evaluated per row
AVERAGEX	Average of expression per row
MINX / MAXX	Min/Max of expression per row
COUNTX	Count of non-blank expression results
RANKX	Rank based on expression
FILTER	Returns table rows matching condition
ADDCOLUMNS	Adds calculated columns to table
SELECTCOLUMNS	Returns table with selected/calculated columns
GENERATE	Cross-join with row context

// Weighted average price
Weighted Avg Price =
SUMX(
    Sales,
    Sales[Quantity] * RELATED(Products[UnitPrice])
) / SUM(Sales[Quantity])

Calculation Groups

Reduce measure sprawl by defining reusable calculation patterns:

// Instead of creating YTD, PY, YoY for EVERY measure:
// Create ONE calculation group with items:
// - Current: SELECTEDMEASURE()
// - YTD: CALCULATE(SELECTEDMEASURE(), DATESYTD(Date[Date]))
// - PY: CALCULATE(SELECTEDMEASURE(), SAMEPERIODLASTYEAR(Date[Date]))
// - YoY%: VAR Curr = SELECTEDMEASURE()
//         VAR PY = CALCULATE(SELECTEDMEASURE(), SAMEPERIODLASTYEAR(Date[Date]))
//         RETURN DIVIDE(Curr - PY, PY)

Create via Tabular Editor, TMDL view in Desktop, or TOM/.NET SDK.

Field Parameters

Enable users to dynamically switch dimensions or measures in visuals:

// Created via Modeling tab > New parameter > Fields
// Generates a calculated table:
Parameter =
{
    ("Revenue", NAMEOF(Sales[Total Revenue]), 0),
    ("Profit", NAMEOF(Sales[Total Profit]), 1),
    ("Units", NAMEOF(Sales[Total Units]), 2)
}

User-Defined Functions (September 2025 Preview)

The most significant DAX language update since variables (2015). Define reusable parameterized functions:

// Define a UDF in DAX query view or model
DEFINE
FUNCTION AddTax = (amount : NUMERIC) => amount * 1.1

// Nest UDFs
FUNCTION AddTaxAndDiscount = (amount : NUMERIC, discount : NUMERIC) =>
    AddTax(amount - discount)

EVALUATE { AddTaxAndDiscount(100, 20) }  // Returns 88

Parameter types: NUMERIC, Scalar, Table, AnyVal, AnyRef, CalendarRef, ColumnRef, MeasureRef, TableRef

Parameter modes: val (eager evaluation) or expr (lazy/context-sensitive)

Usage: Once defined and saved to the model, call UDFs from measures, calculated columns, visual calculations, and other UDFs.

Enable: File > Options > Preview features > DAX user-defined functions

Window Functions (WINDOW, INDEX, OFFSET)

DAX window functions for row-relative and range calculations:

// Running total using WINDOW
Running Total =
CALCULATE(
    [Total Sales],
    WINDOW(1, ABS, 0, REL, ALLSELECTED(Date[Month]),
        ORDERBY(Date[MonthNumber], ASC))
)

// Previous row value using OFFSET
Previous Month Sales =
CALCULATE(
    [Total Sales],
    OFFSET(-1, ALLSELECTED(Date[Month]),
        ORDERBY(Date[MonthNumber], ASC))
)

// Nth row using INDEX
First Month Sales =
CALCULATE(
    [Total Sales],
    INDEX(1, ALLSELECTED(Date[Month]),
        ORDERBY(Date[MonthNumber], ASC))
)

Key clauses:

• ORDERBY -- sort order within the window
• PARTITIONBY -- subset of rows (the "window" partition)
• MATCHBY -- identify the current row in ambiguous contexts

Visual Calculations (2024-2026)

Calculations scoped to the visual matrix, not the data model:

Function	Purpose
FIRST	Value from first row of axis
LAST	Value from last row of axis
PREVIOUS	Value from previous row
NEXT	Value from next row
LOOKUP	Value with filter (June 2025)
LOOKUPWITHTOTALS	Value with filter, respects totals (June 2025)

Visual calculations are defined per-visual and do not affect the semantic model.

Calendar-Based Time Intelligence (September 2025 Preview)

Define custom calendars (fiscal, retail, 13-month, lunar) with 8 new week-based functions:

Function	Purpose
TOTALWTD	Week-to-date running total
CLOSINGBALANCEWEEK	Closing balance for the week
OPENINGBALANCEWEEK	Opening balance for the week
STARTOFWEEK	First date of current week
ENDOFWEEK	Last date of current week
NEXTWEEK	Table of dates for next week
PREVIOUSWEEK	Table of dates for previous week
DATESWTD	Week-to-date date filter

Enable: File > Options > Preview features > Enhanced DAX Time Intelligence

Dynamic Format Strings

Apply context-dependent formatting without converting to text (GA in Desktop and Report Server Jan 2025+):

// Dynamic format string for currency
Total Sales =
SUM(Sales[Amount])

// Format string expression (set in measure properties):
// = IF(SELECTEDVALUE(Currency[Code]) = "EUR", "€#,##0.00", "$#,##0.00")

Advantage over FORMAT(): Keeps numeric data type, enabling correct chart rendering and sorting.

TABLEOF and NAMEOF (February 2026)

Reference model objects that auto-adapt to renames:

// NAMEOF returns the name of a column/measure/calendar as text
NAMEOF(Sales[Amount])  // Returns "Amount"

// TABLEOF returns a reference to the table of a column/measure
TABLEOF(Sales[Amount])  // Returns reference to Sales table

Useful inside UDFs for safer, rename-proof code.

Common Anti-Patterns

Anti-Pattern	Problem	Fix
FILTER(table, ...) as CALCULATE arg	Full table scan, no engine optimization	Use boolean filter: column = value
Nested CALCULATE	Confusing context overrides	Use single CALCULATE with multiple filters
SUMX over entire table for simple sum	Unnecessary iterator	Use SUM() for simple column aggregation
FORMAT() in measures for sorting	Returns text, cannot sort numerically	Use separate sort column
Calculated columns for aggregation	Stored per row, wastes memory	Use measures instead
COUNTROWS(FILTER(table,...))	Slower than CALCULATE(COUNTROWS(table), filter)	Use CALCULATE with filter
Copy-pasting DAX across measures	Hard to maintain, error-prone	Use UDFs (preview) to define reusable logic
FORMAT() for conditional display	Returns text, breaks sorting/charts	Use dynamic format strings instead
Overusing EARLIER()	Confusing, legacy pattern	Use VAR to capture outer context
Ignoring MATCHBY in window functions	Ambiguous row identity	Always specify MATCHBY when partition has duplicates

Additional Resources

Reference Files

• references/dax-function-categories.md -- Complete function reference organized by category including INFO functions, window functions, and 2025-2026 additions
• references/dax-patterns-advanced.md -- Advanced patterns: virtual relationships, dynamic segmentation, parent-child hierarchies, basket analysis