AI/ML, Cloud Computing, Data Analytics

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Powering Calculations and Predictions with DAX

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Overview

DAX is a programming language used to create calculated columns, measures, and custom tables through Power BI by Microsoft.

It is used to solve several calculations and data analysis problems which provide new information from the existing data present in the model.

 

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Introduction

  • DAX is an acronym for Data Analysis Expressions. DAX is used as expressions and formulas for calculating and predicting data, as it can be any data.
  • DAX can also be called Functional Language in Power BI. That means we can put every piece of code in a function. Also, we can use conditional statements, variables, operators and nested functions, etc. These all can be a part of DAX expression.
  • DAX formulas can also be used in measures, calculated columns, and calculated tables.

Ex. Sum of Sales = SUM (Orders [Sales])

  • In the above formula

Sum of Sales – is the name of the measure.

Orders – is the name of the table.

SUM – is a built-in function.

Sales – is the name of the field in the Orders table.

Measures

  • These are dynamic calculation formulas where the values are changed depending on context. It is mainly used in reporting.
  • Some predefined formulas, such as SUM, DIVIDE, and COUNT, can be used in a measure.

Ex. Total Sales = SUM (Sales [Sales Amount])

Calculated Columns

  • You can add any number of columns to an existing table using the Calculated Columns It’s only possible to add columns in the model designer.
  • Qtr.” & Quarter (Calendar [Date])

Calculated Tables

  • It is called a computed The main use of a calculated table is instead of querying and loading values into your new table’s columns from a source, here DAX formulas define the table’s values.
  • It also supports relationships between different tables. These can be re-calculated if any data in the tables are updated.

Some useful DAX Functions

diff1

Types of Functions in DAX

diff2

Benefits of DAX

  • With the help of DAX, Power BI developers can create visualization and reports, providing deeper insight into the data.
  • It mainly solves business problems by predicting the data from the data model using different functions in formulas.
  • Easy to learn.
  • You can make smarter to your dashboard.
  • Speed up your dashboard by using DAX measures.
  • DAX can be used in tabular Microsoft products like Powe BI, Microsoft Analysis Services, and Microsoft Power Pivot for Excel.

Conclusion

DAX supports various types of data for predicting and analyzing the data. Before getting into Power BI Desktop Application, you should know in detail all the concepts of DAX Measures described in this blog. You don’t need to be a programmer to learn these basic concepts of DAX. 

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CloudThat is an award-winning company and the first in India to offer cloud training and consulting services worldwide. As a Microsoft Solutions Partner, AWS Advanced Tier Training Partner, and Google Cloud Platform Partner, CloudThat has empowered over 850,000 professionals through 600+ cloud certifications winning global recognition for its training excellence including 20 MCT Trainers in Microsoft’s Global Top 100 and an impressive 12 awards in the last 8 years. CloudThat specializes in Cloud Migration, Data Platforms, DevOps, IoT, and cutting-edge technologies like Gen AI & AI/ML. It has delivered over 500 consulting projects for 250+ organizations in 30+ countries as it continues to empower professionals and enterprises to thrive in the digital-first world.

FAQs

1. How many types of DAX measures are divided?

ANS: – There are two types of DAX measures implicit measures and explicit measures.

2. Why is the Explicit measure type much better than the implicit measure type?

ANS: – Because Explicit measure type provides features like Control, Reuse, and Connected Reports.

WRITTEN BY Sridhar Andavarapu

Sridhar Andavarapu is a Senior Research Associate at CloudThat, specializing in AWS, Python, SQL, data analytics, and Generative AI. With extensive experience in building scalable data pipelines, interactive dashboards, and AI-driven analytics solutions, he helps businesses transform complex datasets into actionable insights. Passionate about emerging technologies, Sridhar actively researches and shares insights on AI, cloud analytics, and business intelligence. Through his work, he aims to bridge the gap between data and strategy, helping enterprises unlock the full potential of their analytics infrastructure.

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