DAX GUIDE: Top 5 DAX Functions to Master Power BI
There are hundreds of DAX Functions in Power BI 😱.
But you don't have to learn them all.
In all my experience working on client projects, I found myself using just these Top 5 DAX Functions most of the time.
And if you give me just a few minutes:
✔️ I will walk you through each one and...
✔️ Show you how to use them
Click Play ▶ below 👇 to watch:
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Video Covers the following topics:
Top 5 DAX Functions to Master Power BI
#5 SUM, COUNTROWS & A Bonus Function ➕
SUM Function
One of the most basic and widely used functions.
Adds up the values in a column.
Example:
TotalSales = SUM(Sales[Amount])
COUNTROWS Function
Counts the number of rows in a table.
Helpful for determining the number of transactions, products, or customers.
Example:
TotalOrders = COUNTROWS(Sales)
Bonus Function: DISTINCTCOUNT
Counts unique values in a column.
Ideal for counting unique customers or distinct product categories.
Example:
Unique Customers = DISTINCTCOUNT(Sales[CustomerID])
You’ll find yourself reaching for these often when working with aggregations in Power BI.
#4 CALCULATE 🔢
The CALCULATE function is considered the most powerful function in DAX because it allows you to modify the context in which your calculations happen.
Key Features:
Used to apply filters to existing measures.
Modifies filter context dynamically.
Works well with SUM, AVERAGE, COUNT, and other functions.
Example:
Find total sales where the region is "West":
TotalSalesWest = CALCULATE(SUM(Sales[Amount]), Sales[Region] = "West")
#3 X Functions: SUMX, MINX, MAXX etc. 🔄
Next, we dive into the world of X functions, including:
SUMX: Calculates the total revenue by multiplying quantity and price for each row before summing it all up.
MINX: Finds the minimum value row by row.
MAXX: Finds the maximum value row by row.
AVERAGEX: Averages an expression across a table.
The X functions work row by row in a table, applying a calculation to each row and then aggregating the results. They are your toolbox for custom calculations.
Example:
TotalRevenue = SUMX(Sales, Sales[Quantity] * Sales[UnitPrice])
Bonus: Mystery X Function 🔮: FILTER
Here’s a mystery function that deserves special mention:
FILTER: Filter should have been called FILTERX, because it is also an iterator function and operates row by row.
Why Use FILTER?
Allows you to apply complex filtering conditions to tables.
Essential for refining data within calculated columns and measures.
Example:
Filter sales data to include only transactions above 100:
FilteredSales = FILTER(Sales, Sales[Amount] > 100)
#2 ALL Function: Hammer & Chisel Versions ⚒️
The ALL function is like having a hammer and chisel for your data models
Types of ALL Functions:
ALL(Table) – Removes all filters from a table. This is the hammer 🔨 (see video for explanation)
ALL(Column) – Removes filters from a specific column. This is the chisel ⛏️ (see video for explanation).
This function is essential when:
You want to compare a specific value to the overall total.
You need to handle scenarios where filters might distort your calculations.
Example:
Calculate total sales, ignoring any filters on Product Table:
Total Sales AllProducts = CALCULATE(SUM(Sales[Amount]), ALL(Product))
#1 Time Intelligence Functions 📅
Time Intelligence functions are a game-changer in Power BI. These include:
TOTALYTD: Calculates year-to-date totals.
SAMEPERIODLASTYEAR: Compares this year’s performance to last year.
DATESMTD: Calculates month-to-date totals.
They let you perform calculations over specific periods. If your reports involve dates or time, these functions are a must-have in your arsenal.
Example:
YTD_Sales = TOTALYTD(SUM(Sales[Amount]), Sales[Date])
Conclusion
Mastering these five DAX functions will significantly improve your Power BI skills and enable you to create advanced analytical models. Whether it’s basic aggregation with SUM, dynamic filtering with CALCULATE, or time-based calculations, these functions will help you become a Power BI Expert.
Scroll up 👆 to watch the Full Video ▶️: Top 5 DAX Functions to Master Power BI and learn how & when to use each of these DAX functions.
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