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Power Query is Excel's built-in technology for connecting to data, cleaning and reshaping it, and then loading the result into Excel or the Data Model. In Excel it appears mainly through the Get & Transform Data tools.
Its biggest advantage is repeatability. Instead of manually cleaning the same report every week or month, you can define the transformation steps once and then refresh the query when new source data arrives.
What does Power Query do?
Power Query can perform three broad jobs:
- Connect to a data source.
- Transform the source data into the structure you need.
- Load the cleaned result into Excel or the Data Model.
Those steps make Power Query particularly useful when the raw data you receive is not immediately suitable for analysis.
Where is Power Query in Excel?
In current desktop versions of Excel, Power Query tools are found on the Data tab, primarily in the Get & Transform Data area.
The exact commands and available connectors can vary between Excel for Windows, Mac and the web, but Microsoft now provides Power Query capabilities across those platforms.
What problems does Power Query solve?
Power Query is useful whenever a repetitive data-cleaning process sits between your source file and the spreadsheet or report you actually want to use.
Examples include:
- removing unnecessary columns from a downloaded report
- filtering out unwanted rows
- fixing data types
- splitting a combined field into separate columns
- combining first name and surname fields
- replacing inconsistent values
- merging information from two tables
- appending several tables with the same structure
- combining monthly files from a folder
- refreshing a report when the source data changes
What is the Power Query Editor?
The Power Query Editor is the workspace where you inspect and transform your data before loading it into Excel.
You see a preview of the data together with the sequence of transformations that have been applied.
Typical editor actions include:
- renaming, removing and reordering columns
- changing data types
- sorting and filtering rows
- splitting or merging columns
- replacing values
- grouping data
- pivoting and unpivoting columns
- merging queries
- appending queries
What are Applied Steps?
Every transformation you perform is recorded as a step in the query.
For example, a query might contain these steps:
- connect to the source workbook
- promote the first row to headers
- change column data types
- remove three unnecessary columns
- filter out cancelled transactions
- replace an inconsistent department name
When you refresh the query, Power Query performs those steps again on the latest version of the source data.
Why is refresh so useful?
Refresh is one of the main reasons businesses use Power Query.
Imagine receiving a CSV export every Friday. Without Power Query, you might open the file, delete columns, change formats, filter rows and copy the cleaned data into another workbook every week.
With Power Query, those cleaning steps can be recorded once. The following week you update or replace the source data and refresh the query.
This does not remove the need to check your results, but it can dramatically reduce repetitive manual processing.
Can Power Query combine multiple Excel files?
Yes. One of its most useful features is the ability to combine files with a consistent structure, including files stored in a folder.
For example, if you receive twelve monthly sales workbooks with the same columns, Power Query can combine them into one dataset. When another compatible file is added to the folder, a refresh can incorporate the new data.
This is often much more reliable than repeatedly copying and pasting data from individual workbooks.
Can Power Query merge tables?
Yes. A merge joins two queries using matching fields.
For example, a Transactions table might contain a Product ID but not the product description or category. A separate Products table could contain that information. Power Query can merge the tables using Product ID and bring the required fields into the result.
This is conceptually similar to performing a lookup, but it happens as part of the data-preparation process.
What is the difference between Merge and Append?
Merge combines tables horizontally by matching a field in one table to a field in another.
Append stacks tables vertically, adding the rows from one table below the rows from another.
If you are combining January and February transaction files with identical columns, you would usually append. If you are adding customer details to a transaction table using Customer ID, you would usually merge.
Power Query vs Excel formulas
Power Query and worksheet formulas are both valuable, but they perform different jobs.
Power Query is usually better for:
- importing external data
- cleaning repeated data extracts
- changing the shape of a dataset
- combining files
- merging or appending tables
- creating a repeatable preparation process
Excel formulas are usually better for:
- calculations that need to appear directly in worksheet cells
- interactive calculations driven by user input
- small ad-hoc calculations
- logic that should update immediately as worksheet cells change
In many workbooks the best solution uses both: Power Query prepares the data, then Excel formulas or PivotTables analyse it.
Power Query vs macros and VBA
Macros and VBA can automate almost any Excel process, whereas Power Query is specifically designed for data connection and transformation.
If your task is primarily importing, cleaning, combining and refreshing data, Power Query is often easier to maintain because the transformation steps are visible in the query.
If you need to automate worksheet formatting, user interactions, file creation or actions outside Power Query's data-preparation role, VBA may be more appropriate.
Power Query vs Power Pivot
This is a common source of confusion.
Power Query prepares the data. It connects, cleans, reshapes, merges and combines.
Power Pivot models and analyses the data. It creates relationships between tables and supports calculations using DAX.
The two tools work extremely well together. Our Power Query vs Power Pivot guide explains the distinction in detail.
Is Power Query the same in Excel and Power BI?
The underlying Power Query technology is shared across Excel and Power BI, so many of the concepts and transformation techniques are transferable.
If you learn how to filter rows, change data types, merge queries or append tables in Excel Power Query, those skills are highly relevant in Power BI.
This is one reason Power Query is a useful stepping stone for Excel users moving towards business intelligence. See Power BI vs Excel for the broader relationship between the products.
Does Power Query require coding?
No. Most everyday Power Query transformations can be created through the graphical interface.
Behind the scenes, Power Query uses the M formula language. Each step is represented by an M expression, but beginners do not need to write M code to start using the tool effectively.
As your skills develop, understanding M can help with transformations that are difficult or impossible to create solely through the interface.
Do you need Power Query if your data is already clean?
Not always. If you have a small dataset that is already in the correct format and never needs to be refreshed, introducing Power Query may add unnecessary complexity.
Its value increases when the preparation process is repetitive, the data comes from an external source, multiple files need to be combined, or the same transformations need to be performed regularly.
What happens to the original data?
Power Query is designed to transform a representation of the data rather than requiring you to manually alter the source file.
The query contains instructions describing how the source should be transformed. The resulting data is then loaded to its destination.
This approach is useful because the raw source can remain separate from the cleaned reporting dataset.
Can Power Query replace copy and paste?
In many recurring reporting processes, yes.
If you repeatedly copy data from one file into another, remove the same columns and perform the same cleanup every month, that is exactly the kind of workflow worth investigating with Power Query.
It can reduce manual effort and also make the process easier to review because the transformation steps are recorded.
Can Power Query handle large datasets?
Power Query is often more practical than manual worksheet editing for larger datasets, but performance depends on the volume and structure of the data, the transformations used, the source system and your Excel environment.
For very large or complex analytical models, you may also need the Excel Data Model, Power Pivot, Power BI or a database rather than relying on a standard worksheet alone.
How should a beginner learn Power Query?
A useful sequence is:
- Import a simple Excel table or CSV file.
- Learn to remove and rename columns.
- Change data types correctly.
- Filter and remove rows.
- Split, merge and replace values.
- Understand Applied Steps.
- Load the query and refresh it.
- Append similar files or tables.
- Merge related datasets.
- Progress to folder imports and more advanced transformations.
Where does Power Query fit in the ExperTrain Excel pathway?
Our Microsoft Excel Power Query course focuses specifically on importing, cleaning, transforming and combining data.
If you are building broader advanced Excel skills, Excel Advanced Functions & Data Modelling develops functions and data-model techniques alongside related analytical tools.
Power Query is also used within Power BI Desktop Intermediate.
Frequently asked questions
Is Power Query free with Excel?
Power Query is integrated into supported current versions of Excel rather than being a separate paid application. Available features and connectors can vary by platform and Microsoft 365 plan.
Is Power Query difficult to learn?
The basics are relatively accessible because most transformations can be created through menus. The learning curve becomes steeper when queries become more complex or you start working directly with M expressions.
Does Power Query automatically update?
Queries can be refreshed to retrieve current source data and repeat their transformation steps. Refresh settings depend on how the workbook and connection are configured.
Can Power Query combine CSV files?
Yes. Power Query can connect to CSV files and can also combine multiple consistently structured files, including files stored in a folder.
Can Power Query do lookups?
Power Query can merge tables using matching keys, which often replaces the need to use worksheet lookup formulas during the data-preparation stage.
Should I learn Power Query before Power Pivot?
For many Excel users, yes. Learning how to create a clean, well-structured dataset first makes later data modelling and DAX work easier to understand.
Next steps
Explore the Excel Glossary for explanations of Excel terminology, take the Excel Skills Assessment if you are unsure which Excel course level is right for you, or read What Is DAX in Power BI? to understand how data preparation and analytical calculations fit together.
Further reading
Microsoft's official support guide provides an overview of Power Query and Get & Transform in Excel: About Power Query in Excel.
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