Getting Started with DAX: A Complete Guide for Power BI Users

DAX (Data Analysis Expressions) is a language you must learn

Whether you are just getting started with Power BI or looking to deepen your understanding of data modelling and calculations, DAX (Data Analysis Expressions) is a language you must learn. In this blog, we will walk through the complete introduction to DAX based on practical knowledge and foundational concepts.

DAX: A Practical Guide

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What is DAX?

DAX is a formula language used in Power BI, Power Pivot, and SSAS Tabular models. It is designed for data models and business calculations.

While DAX looks similar to Excel formulas, it introduces a different type system and does not operate with the concepts of traditional "rows" and "columns" as in spreadsheets.

Key Characteristics:

• Functional language

• Executes through function calls

• Often used to define Calculated Columns, Measures, and Calculated Tables

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Understanding DAX Syntax

Here is a classic example of a DAX formula:

= SUMX(
    FILTER(VALUES('Date'[Year]), 'Date'[Year] < 2005),
    IF('Date'[Year] >= 2000, [Sales Amount] * 100, [Sales Amount] * 90)
)

Important Tip: Proper formatting is critical in DAX. Use DAXFormatter to maintain clean and readable code.

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Calculated Columns vs. Measures

Feature Calculated Column Measure Context Evaluated row-by-row Evaluated based on filter context Storage Uses memory Uses CPU during query execution Syntax Table[Column] [Measure] Use Case Filtering and slicing Aggregations, percentages, ratios

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Aggregation Functions

Standard aggregators:

• SUM

• AVERAGE

• MIN

• MAX

These work on numeric columns and evaluate only one column at a time.

X Aggregation Functions (Iterators):

• SUMX, AVERAGEX, MINX, MAXX

• Accept a table and an expression

Example:

SUMX(Sales, Sales[Price] * Sales[Quantity])

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Using Variables in DAX

Variables reduce code duplication and improve readability:

VAR TotalQty = SUM(Sales[Quantity])
RETURN
IF(TotalQty > 1000, TotalQty * 0.95, TotalQty * 1.25)

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Working with Dates

DAX has robust support for date and time functions:

• YEAR, MONTH, NOW, TODAY

• DATESYTD, SAMEPERIODLASTYEAR, TOTALYTD

Make sure your data model includes a complete Date table for time intelligence functions to work.

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Table Functions

Functions that return tables instead of values:

• FILTER

• ALL

• VALUES

• DISTINCT

• RELATEDTABLE

Example:

SUMX(
    FILTER(Orders, Orders[Price] > 1),
    Orders[Quantity] * Orders[Price]
)

ALL() removes filters and returns all rows:

SUMX(
    ALL(Orders),
    Orders[Quantity] * Orders[Price]
)

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The CALCULATE Function

The CALCULATE function modifies filter context and is considered the most powerful function in DAX.

CALCULATE(
    SUM(Sales[SalesAmount]),
    Sales[SalesAmount] > 100
)

Equivalent using FILTER:

CALCULATE(
    SUM(Sales[SalesAmount]),
    FILTER(ALL(Sales[SalesAmount]), Sales[SalesAmount] > 100)
)

You can clear filters on individual columns:

CALCULATE(
    SUMX(Orders, Orders[Amount]),
    ALL(Orders[Channel])
)

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Evaluation Contexts

Filter Context

Determined by:

• Row/column selections

• Report filters and slicers

• Manual functions like CALCULATE, ALL, FILTER

Row Context

Occurs:

• In calculated columns

• When using iterators like SUMX, AVERAGEX

Context Transition

When CALCULATE is used within a row context, it creates a filter context from that row. This is known as context transition.

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Relationships and Context

Relationships in your data model affect how filters and rows are evaluated:

• Filter context does propagate over relationships

• Row context does not

Use RELATED and RELATEDTABLE to access columns across related tables.

Example:

COUNTROWS(
    FILTER(RELATEDTABLE(Product), Product[Color] = "Red")
)

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Time Intelligence

For advanced analytics, use built-in Time Intelligence functions like:

• DATESYTD

• SAMEPERIODLASTYEAR

• TOTALYTD

• CALENDARAUTO

Examples:

SalesAmountYTD :=
CALCULATE(SUM(Sales[SalesAmount]), DATESYTD('Date'[Date]))

Sales_SPLY :=
CALCULATE(SUM(Sales[SalesAmount]), SAMEPERIODLASTYEAR('Date'[Date]))

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Conclusion

DAX is not just a language—it’s the engine that powers the intelligence in your data models. By learning how to use DAX for calculated columns, measures, filters, and time intelligence, you take full control over your Power BI insights.

Start simple, format your code well, and explore more advanced topics like context transition and calculated tables as you grow. Whether you're preparing for interviews or building enterprise dashboards, DAX will be your most powerful tool.

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Want more? Stay tuned for upcoming posts where we deep dive into real-world DAX scenarios, performance tuning tips, and common DAX mistakes to avoid.

Disclaimer: This post is based on foundational DAX training materials used in various BI educational resources. The content has been restructured and rewritten for educational and informational purposes only.

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