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by Pradeep Kumar Kasipuri

Last modified: March 31st 2021

Do you know why the DAX in Power BI plays a vital role in data analytics? How does the creation of custom measures impact your decision making?

Well, You might’ve import some data into Power BI desktop files and even create reports that show valuable insights. But what if, you need to analyze growth (%) of product lists over different date ranges or, need to analyze annual growth of your company compared to rivals. This is where Power BI DAX comes into the picture.

In this blog, we’re going to discuss the most useful DAX functions in Power BI and the creation of measures by using Power BI desktop and more.

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In this Power BI DAX Basics Article, we will discuss the following topics:

**DAX in Power BI: How does it work?**

**DAX in Power BI: Calculated Columns & Measures**

**Calculated Columns vs Measures**

**Power BI DAX Basics: Types of Functions in DAX**

**Aggregate Functions****Count Functions****Date-Time Functions****Math Functions****Logical Functions****Information Functions****Text Functions**

**Creating a Measure using Power BI DAX**

**Power BI DAX Tutorial | DAX Basics in Power BI | DAX Functions in Power BI**

So, let us begin with the DAX definition first, which I am going to talk about in the section below.

Data Analysis Expressions (DAX) is a syntax language that comprises formulae and expressions that are used in data manipulation. Functions, constants and operators are used in DAX to create expressions. In simpler terms, DAX is the advanced version of MS Excel with high-end data manipulation and management capabilities. It is developed by Microsoft to interact with its business intelligence and data modelling tools like PowerPivot, Power BI. Power BI is a robust analytics tool by Microsoft that offers several features and functions using DAX as a language.

**Some of the major advantages of Power BI are:**

- Real-time data visualization
- Creation of charts and report generation on voice command using Cortana
- Large storage space and easy retrieval of data from the storage
- Higher security at the Row level
- BI has intuitive user experience features and memorizes most frequently used trends

All these functions are essentially performed by pre-set tools and commands in the system. But there are several occasions when you want to perform a particular type of function says a certain type of data analysis but you are unable to do so because the command does not pre-exist in the system. What do you do in such a case? This is where DAX comes into the picture.

DAX is quite an important syntax as working in DAX improves the user experience by deploying functionalities like data visualization, data importing and manipulating. For normal report creation, the basic knowledge of the dashboard is enough but to be able to build up sophisticated and insightful reports, DAX is required. With several commands and measures that can be used under the DAX syntax, the reports generated are highly intuitive and discerning.

DAX works on a combination of three fundamental concepts:

- Syntax
- Context
- Functions

These inputs are fundamental to the creation of a specific command that fetches desired results.

Syntax refers to the components of the formula you are making. It is the language used in the formula like the command, sign, operators, destination column or row or table, etc. For example, name, parenthesis, summation, name of the table, etc.

Context refers to the target row that has been included in the formula for data retrieval or calculation. Context is present in two types: Row Context and Filter Context.

Functions refer to the predefined or already existing commands in the system. For example, Sum, Add, True, False, etc.

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In this Article, we are going to be focusing on the Power BI DAX formulae used in calculations, in Measures and Calculated Columns.

Similar to other regular columns, calculated columns are the ones that come out as a result of computations within two columns of different data sets. They are ideal for row-wise calculations;

Calculated columns are ideal for dynamic calculations as they do not acquire any physical space. These are used when data in rows are grouped together for computations.

Calculated columns and calculated measures both use DAX expressions for data manipulation. The difference lies in the context of the underlying formula. In the calculated column type, the calculation takes place at the row level within a given table. In the calculated measure type, the calculation is done at the cell level in the entire report or the query.

**MIN**

Fetches the minimum value in a given column.

*Syntax *

`MIN(<column>)`

*Example *

`=MIN( [ SellerMargin] )`

**MINA**

Fetches the minimum value along with Aggregate Functions Logical values and text representation of numbers if any

*Syntax*

`MINA( <column> )`

*Example*

`=MINA( InternetSales[Freight] )`

**MINX**

Fetches the minimum value after evaluation of each row expression in a given table.

*Syntax*

`MINX ( < table >, <expression> )`

*Example *

` =MINX( FILTER( InternetSales ) , [ SalesTerittoryKey ] = 2 , [Freight] )`

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**Other functions**

**MAX**

**MAXA**

**MAXX**

**SUM**

**AVERAGE**

**SUMX**

**AVERAGEX**

**DISTINCTCOUNT**

Fetches the count of distinct numbers avoiding any replication.

**Syntax**

`DISTINCTCOUNT( <column> )`

*Example*

`=DISTINCTCOUNT( ProductsList[ProductID] ) `

**COUNT**

Fetches the total count of items even if repetitions are present.

*Syntax*

` COUNT( <column> )`

*Example*

`=COUNT ( [ShipDate] ) `

**COUNTA**

Fetches the count of items in a non-empty column.

*Syntax*

`COUNTA( <column> )`

**Example**

`= COUNTA( ‘ProductSeller’[Phone] ) `

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**COUNTROWS**

Fetches the number of rows in a given table.

*Syntax*

`COUNTROWS( < table > )`

*Example*

`=COUNTROWS( ‘Enquiries’ )`

**DATE**

Fetches the desired date in Date-time format.

**Syntax**

`DATE ( <year>, <month>, <day> )`

*Example*

`=DATE ( 2020,02,27 ) `

**HOUR**

Fetches hours in the AM PM format.

*Syntax*

`HOUR ( <datetime> )`

*Example*

`=HOUR( ‘Orders’ [TransactionTime] )`

**TODAY**

Fetches the current date.

*Syntax*

`TODAY()`

*Example*

` = YEAR ( TODAY())-2012`

**Other functions**

**NOW**

**EOMONTH**

**ABS**

Fetches the absolute value.

*Syntax*

`ABS( <number> )`

*Example*

`=ABS( [LabelPrice] - [SellingPrice] ) `

**EXP**

Fetches the exponents value.

*Syntax*

`EXP( <number> )`

*Example*

`=EXP( [Power] ) `

**FACT**

Fetches the factorial of a given number.

*Syntax*

`FACT( <number> )`

*Example*

`=FACT( [Values] )`

**Other functions**

**LN**

**LOG**

**PI**

**POWER**

**QUOTIENT**

**SIGN**

**SQRT**

**AND**

Performs the logical conjunction on two specified expressions.

*Syntax*

`AND( <logical1> , <logical2 > )`

*Example*

` =IF( AND(1<2 , 2<3) , “All true” , “One or false” ) `

**OR**

Performs the logical disjunction on two specified expressions.

*Syntax *

`OR( <logical1 > , <logical2 > )`

*Example*

`=( IF(OR(1<2 , 2<3) , “All true” , “One or more false” ) `

**NOT**

Performs logical negation on the given expression.

*Syntax*

`NOT( <logical > )`

*Example*

` =NOT( [ProductPrices] )`

**Other functions**

**IF**

**IFERROR**

**ISBLANK**

Declares if the value is blank or not as true or false.

*Syntax*

`ISBLANK( <value> )`

*Example*

`=IF( ISBLANK(‘CalculatedMeasures’[PreviousYearTotalSales]) ,BLANK() , (CalculatedMeasures’[PreviousYearTotalSales]/ ‘CalculatedMeasures’[PreviousyearTotalSales])`

**ISNUMBER**

Declares if the value is a number or not.

*Syntax*

`ISNUMBER(<value>)`

*Example*

`=IF( ISNUMBER(2), “Is number”, “Is Not number” ) `

**ISNONTEXT**

Declare if the value is non-text.

*Syntax*

` ISNONTEXT( <value> )`

*Example*

`=IF( ISNONTEXT(“ ”), “Is Non-Text”, “Is Text” )`

**Other functions**

**ISERROR**

**ISTEXT**

**CONCATENATE**

Performs joining of two strings.

*Syntax*

`CONCATENATE( <text1> , <text2> )`

*Example*

`= CONCATENATE( “Hello” , “Learner” ) `

**FIXED**

Performs rounding off of number to a given decimal.

*Syntax*

`FIXED( <number> , <decimals> , <no_commas> )`

*Example*

`=FIXED( [LabelPrice], 3,1 ) `

**REPLACE**

Replaces part of a string with specified characters.

*Syntax*

`REPLACE( <old_text> , <start_num>, <num_chars> , <new_text> )`

*Example*

`=REPLACE( ‘New Services’[Service ID],2,3,”AB” )`

**Other functions:**

**SEARCH**

**CONCATENATEX**

**SEARCH**

**UPPER**

*The following steps make your task simple to create a measure using Power BI DAX.*

**1**. First, go to the **Power BI Desktop app.**

**2**. Right-click the Sales table or hover over** More options** (...) of **Field** pane.

**3**. Once the menu presents, select **New Measure**. This activity stores the new Measure in the** Sales **table. You can also create a new Measure from Power BI desktop ribbon in the following way.

Go to **Home** tab > **Calculations** group >** New Measure.**

**4**. Next, the Formula bar exists on top of the reporting canvas, where you can edit your name and write a Data Analysis Xpression formula.

Let’s discuss the concept before creating the formula. This makes you simple to proceed further

**Variables Selection and Formula creation:**

- The net amount of any products or services requires some variables.so, I listed out prerequisite variables: Net Amount, Quantity of products or services, price of each quantity and other expenditure(Total cost price).
- Net amount = (Total Quantity Sales) * (Per/Product or Service) - Expenditure (cost price).

**5**. The Measure is named by default in the formula bar, but we need Measure to be more noticeable, emphasize Measure in the formula bar and alter it to Net Amount.

**6**. While creating your formula, write Sum after the equal sign. Now, the drop-down suggestion list appears, once you type the starting of the letter. Select from the list, if needed and then press **Enter.**

**7**. Press enter after typing the SUM. Now, you can see an open parenthesis along with a drop-down suggestion list of existing columns. It can be passed to the SUM function.

**8**. The expression always between Open parenthesis and Closing parenthesis. For this instance, your expression comprises an argument to push to the SUM function: the SalesQuantity Column. Start Typing **SalesQuantity** until** Sales[SalesQuantity]** is the only value that appears in the list.

The Table name is preceded by the column name is called the fully qualified name of column . It makes your formula easier to comprehend.

**9**. Select **Sales[Sales quantity]** from the list then enter closing parenthesis.

**Multiply the Value with the First Expression and Subtract other Column from the Final Value:**

- After finishing the first expression, multiply 15,000 with that expression to obtain the total amount of the quantity.

**Sales[SalesQuantity]* 15000. **

- Type a space after the desired value, space, a minus operator (-) and then another space.
- Write another SUM function, and Start writing TotalCost you can select the
and then enter closing parenthesis.**Sales[TotalCost]**

**10**. To finish and validate the formula, we need to enter either **Enter** or Select CheckMark icon(**Commit).**

The validated **Net Amount** measure is now ready to use in the sales table in the **Fields pane**.

**Conclusion**

DAX is one of the most commonly used expression syntax these days with a wide range of applicability. Learning it opens up several opportunities in the market especially in the SQL enabled companies. With DAX in Power BI, you are empowered to build up any kind of logical expression or formula as per requirement.

Reach out to us in comments if you want to learn and excel in DAX.

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