You don't need to master M immediately. Start by understanding the transformations available through the interface.

🔹 13. Merge Queries

Merge Queries combines related tables using a common column.

For example:

Customers

Customer_ID | Customer_Name

101 | John

102 | Sarah

Orders

Order_ID | Customer_ID | Sales

1 | 101 | 5000

2 | 102 | 7000

You can merge them using:

Customer_ID

This is similar to a SQL "JOIN".

🔹 14. Append Queries

Append combines tables by adding rows.

For example:

January Sales

↓

February Sales

↓

March Sales

becomes one table containing all three months.

Remember:

Merge → Combine columns

Append → Combine rows

🔹 15. Applied Steps

Power Query records every transformation you perform.

For example:

Source

↓

Changed Type

↓

Removed Columns

↓

Filtered Rows

↓

Trimmed Text

↓

Removed Duplicates

This makes the cleaning process repeatable.

When the source data is refreshed, Power Query can apply the same steps again.

🔹 16. Query Folding

Query Folding is an important performance concept.

When possible, Power Query pushes transformations back to the source system.

For example:

Power BI

↓

Filter 2026 Data

↓

Database performs filtering

↓

Power BI receives required data

This can reduce the amount of data transferred and improve refresh performance.

Query folding depends on the data source and the transformations being used.

🔹 17. Power Query vs SQL vs DAX

Remember this simple difference:

SQL

→ Retrieve and analyze data from databases

Power Query

→ Clean and transform data

DAX

→ Create calculations and analyze data inside the Power BI model

A typical workflow is:

SQL

↓

Get Data

Power Query

↓

Clean & Transform

Data Model

↓

Create Relationships

DAX

↓

Create Measures

Visuals

↓

Build Report

🎯 Interview Question

What is the difference between Merge and Append in Power Query?

Merge combines related tables using matching columns.

Append stacks tables with similar structures by adding rows.

Merge → More columns

Append → More rows

💡 Key Lesson

Power Query prepares your data so that your Power BI model and reports are built on clean, reliable data.

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