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Product Sales = SUMX( RELATEDTABLE(Sales), Sales[SalesAmount] ) 🔹 Iteration Functions Functions ending in X are called iterator functions. 17. SUMX Calculates an expression row by row and then adds the results. Total Revenue = SUMX( Sales, Sales[Quantity] * Sales[Price] ) If a row has: Quantity = 5 Price = 1000 Revenue for that row = 5000. SUMX then adds the results across all rows. 18. AVERAGEX Calculates an expression for each row and returns the average. Average Revenue = AVERAGE…

📊 Power BI — Essential DAX Functions with Examples DAX is used for calculations in the Power BI data model. These are the functions you should learn first. 1. SUM Adds values from a column. Total Sales = SUM(Sales[SalesAmount]) Use it when you need the total sales amount. 2. AVERAGE Returns the average value. Average Sales = AVERAGE(Sales[SalesAmount]) 3. COUNT Counts numeric values. Order Count = COUNT(Sales[OrderID]) 4. COUNTROWS Counts the number of rows in a table. Total Orders…

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Mistake 4: Not testing the function Always test your function with a few inputs before applying it to hundreds of files. 🧪 Practical Exercise Create a simple function that calculates profit margin. Use: • Sales • Cost Formula: (Sales - Cost) / Sales For example: Sales = ₹10,000 Cost = ₹7,000 Profit Margin: (10000 - 7000) / 10000 = 0.30 = 30% Then test your function with different Sales and Cost values. After that, think about how you could use the same concept to transform multi…

Now you can provide both the price and tax rate. For example: CalculatePrice(1000, 0.18) Result: 1180 And: CalculatePrice(1000, 0.05) Result: 1050 The function becomes more flexible. 6. Custom Functions with Tables Custom functions become especially powerful when working with tables. Imagine you receive these files: January.xlsx February.xlsx March.xlsx April.xlsx Each file contains raw sales data. You want every file to go through the same cleaning process. You can create a f…

📊 Power BI Learning Roadmap — Part 4 Topic 13: Custom M Functions After learning the basics of M language, the next important concept is Custom Functions. Custom functions allow you to write a transformation once and reuse it multiple times. This becomes very useful when you have many files or tables that need the same transformation logic. 1. What Is a Custom Function? A custom function is a reusable piece of M code that accepts an input and returns an output. For example, suppose you fr…

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These functions become much easier to understand once you recognize the pattern. 7. The each Keyword You will see each frequently in Power Query. For example: each [Sales] > 5000 It means the expression should be evaluated for each row. Another example: each [Quantity] * [Price] This calculates the result for every row. If: Quantity = 10 Price = 500 then: 10 × 500 = 5000 8. Column References In M, a column can commonly be referenced like: [Sales] For example: each [Sales] * 1.1…

📊 Power BI Learning Roadmap — Part 4 Topic 12: Power Query M Language Until now, we have mostly used the Power Query interface to clean and transform data. But behind almost every transformation you perform in Power Query, there is code. That language is called M. Understanding M doesn't mean you need to become a programmer. You just need to understand how Power Query represents the transformations you perform. 1. What is M Language? M is the language used by Power Query for data transfor…

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If you have two tables: January Sales and February Sales Use: Home → Append Queries → Append Queries as New Then select the two queries. 8. Append Three or More Queries You can also append more than two tables, for example January to June. All can be combined into one Sales table. This is useful when monthly data is stored separately. 9. What If Column Names Are Different? Suppose January contains Product Sales and February contains Product Revenue. Power Query treats Sales and Revenue as …

📊 Power BI Learning Roadmap — Part 4 Topic 10: Merge Queries and Append Queries in Power Query When working with real-world data, you rarely get everything in one table. You may have: • Sales data in one table • Product information in another • Customer information in another • Monthly sales in separate files Power Query provides two important features to combine these datasets: 1. Merge Queries 2. Append Queries The key difference is simple: • Merge Queries = add columns from anothe…

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