Reviewed and fact-checked by Sayantoni Das

Power Query makes solving common data tasks easy. A lot of precious time is usually spent on repetitive manual work such as cut & paste tasks or combining columns and applying filters. The Power Query tool makes it a whole lot easier to perform such tasks. 

An added benefit here is that Power Query is easy to use when compared to other BI tools. The Power Query interface is user-friendly. Since it is very similar to the Excel interface, many users will find it comfortable.

Become The Highest-Paid Business Analysis Expert

With Business Analyst Master's ProgramExplore Now
Become The Highest-Paid Business Analysis Expert

What is Power Query?

Power Query is an application for transforming and preparing data. With Power Query you can get data from sources using a graphical interface and apply transformations using a Power Query Editor. Using Power Query, a business intelligence tool offered by Microsoft Excel, you can import data from any number of sources, clean it, transform it, then reshape it according to your needs. In this way, you can set up a query only once, re-use it later by simply refreshing.

As the name suggests, Power Query is the most powerful data automation tool found in Excel 2010 and later. Power Query allows a user to import data into Excel through external sources, such as Text files, CSV files, Web, or Excel workbooks, to list a few. The data can then be cleaned and prepared for our requirements.

Power Query has several useful features embedded in it, such as the appending of data and creating relationships between different data sets. This is called the merging of the data sets. We can also group and summarize data with the help of the tool. Needless to say, it is a very useful tool.

powerQueryLogo_PowerQuery

How Do You Enable Power Query?

Power Query is available as a free add-in on Excel 2010 and 2013, which you can download from Microsoft's website. The link is available here.

On clicking the Download button, a dialog box opens where you can choose the appropriate download option that suits your OS. Power Query will then be downloaded on your system.

It is a built-in tool starting with Excel 2016 and is available in the Get & Transforms Data Section under Data Tab. 

The Four Phases of Power Query

Power Query allows users to extract, transform, and load (ETL) data from various sources into Excel or Power BI. The four phases of Power Query are:

1. Connect

In this phase, users connect to the data source(s) from which they want to extract data. Power Query supports many data sources, including databases, files, web pages, and more. Users can also specify any required authentication or authorization details during this phase.

2. Transform

Once the data is loaded into Power Query, users can use various data transformation tools to clean, reshape, and transform the data to meet their specific needs. Common data transformation tasks include removing duplicates, filtering data, merging data, splitting columns, and pivoting data.

3. Combine

Power Query also allows users to combine data from multiple sources using various techniques. Users can merge tables, append, or join data using a common key. This phase is beneficial for integrating data from different sources into a single, unified view.

4. Load

Finally, in the Load phase, users specify where to load the transformed data. They can load the data into an Excel worksheet or a Power BI report or create a connection to the data source so that the data is automatically refreshed whenever the source data changes.

Let’s move forward and understand the concept of Power Query. 

What is a Query List?

A query list refers to a collection or set of queries within a database or data management system. It represents a group of predefined queries that are saved and organized for easy access and execution. A query list typically includes a series of query statements or commands that retrieve, filter, sort, or manipulate data from one or multiple tables or data sources. Query lists provide a convenient way to store and manage frequently used or complex queries, allowing users to quickly execute them without the need to recreate or modify the queries each time. They enhance efficiency, consistency, and reusability in data querying and analysis processes.

Data Preview:

Data Preview in Power Query refers to the visual representation of the imported data within the Power Query Editor window. It allows users to see a sample of the data before applying any transformations, providing a quick overview of the dataset's structure and contents. The Data Preview section displays the first few rows of the imported data, along with the column headers, enabling users to assess the quality and suitability of the data for further analysis or manipulation.

Applied Steps

Applied Steps in Power Query are the sequence of actions or transformations that have been applied to the imported data. Each step represents a specific operation, such as filtering, sorting, renaming columns, or merging queries. The Applied Steps section in the Power Query Editor displays a list of these transformations in the order they were applied. Users can review, modify, or remove individual steps to refine the data preparation process and achieve the desired output. Applied Steps provide transparency and reproducibility, allowing users to track and reproduce data transformations easily.

Formula Bar

The Formula Bar in Power Query is a section within the Power Query Editor that allows users to view and edit the formulas associated with each step or transformation. It provides a text-based representation of the applied transformations, enabling users to manually input or modify the underlying M language code that defines the data transformations. The Formula Bar offers a more advanced and precise way to manipulate data by leveraging the full capabilities of the M language. It is particularly useful for complex or custom transformations that cannot be achieved through the graphical user interface alone.

What Can You Do With Power Query?

Power Query is a widely used ETL(Extract, Transform, Load) tool. Let’s look at the three basic steps.

1. Get Data

Importing data is easy with the help of the Get & Transform Data section of the Data tab in Excel. 

transform_PowerQuery.

You can import data from several different sources.

  • From Files: Excel files(Workbook), Text or CSV files, XML files, and JSON files.
  • From Databases: SQL Server, Microsoft Access, SQL Server Analysis Services.
  • From Other Sources: Excel Tables/ Ranges, Web, Microsoft Query, OData feeds.

get_data_PowerQuery

2. Transform Data

After importing the data, we can transform it with the help of Power Query. The Power Query Editor helps you transform data based on your needs.

Let’s take a look at the editor and understand its different components.

The Power Query Editor Interface

power_query_editor_PowerQuery

Become The Highest-Paid Business Analysis Expert

With Business Analyst Master's ProgramExplore Now
Become The Highest-Paid Business Analysis Expert

The six main sections of the Power Query Editor are as follows:

  • Query Editor Ribbon:  This ribbon is similar to the one on the Excel interface. Various commands are organized in separate tabs.  
  • Query List: This section lets you browse through a list of all queries in your current workbook.
  • Formula Bar: The current transformation’s formula will be specified here in the M language.
  • Data Preview: You can see the preview of your data based on the current transformation step. You can access various transformation commands by right-clicking on the column header or by clicking on the respective column header's filter option.
  • Properties: This section consists of a list of query steps. Here, you will be able to name your query. Naming a query is an important step to identify a query easily.
  • Applied steps: Each transformation step you take will be recorded here in chronological order. You can add, remove, edit, or reorder the steps if required.

This was all about the editor interface. Now, let’s proceed by understanding a simple transformation example on the Editor.

Follow the steps below to learn how to sort a table based on a single column.

  • First, load the data onto the Editor.
  • Then, select the column you want to sort.
  • Click on the filter icon, as shown in the image.

transformation_1

transformation_2

  • On clicking OK, the table gets sorted based on the ‘Name’ column alphabetically.

You will see the M code in the formula bar. This is used to record the steps applied. 

transformation_3.

  • The applied transformations will reflect in the ‘Applied Steps’ section.

/transformation_4.

Numerous other transformations can be performed on the Editor. After this step, we need to load the data onto our Excel spreadsheet. 

3. Output to Excel

After performing all the operations on the editor, we will have to output it to our Excel sheet. To do this, click on the Close and Load option on the Ribbon section of the Power Query Editor.

load_data.

On clicking this option, the Editor closes and loads the result to your worksheet.  

In the next section, we will look at different ways by which we can Import Data to our Excel sheet.

Become The Highest-Paid Business Analysis Expert

With Business Analyst Master's ProgramExplore Now
Become The Highest-Paid Business Analysis Expert

Different Ways to Import Data to the Excel Sheet

Listed below is a detailed tutorial of importing data from various data sources.

1. Importing Data from a Text File

getData_textFile_PowerQuery.

Follow the steps to import a text file using Power query:

  • Click on the Data tab --> Text/CSV File.
  • Once we have selected the “Text/CSV file” option, an ‘Import data’ dialog box is opened.
  • Select the desired text file and click on Import.
  • A dialog box is opened, which shows a preview of the data contained.
  • Finally, click on Load to import the data.

2. Importing Data From a CSV File

getData_csv_PowerQuery

You can use Power Query to import from CSV files by following the steps below:

  • Click on the Data tab --> Text/CSV File.
  • Once we have selected the “Text/CSV file” option, an “Import data” dialog box is opened.
  • Select the desired CSV file and click on import.
  • A dialog box is opened, which shows a preview of the data contained.
  • Finally, click on Load to import the data.

3. Importing a Single Data Source From an Excel Workbook

To import a Single Data Source, follow these steps:

  • Click on the Data tab --> Get Data command. This opens up a drop-down menu. The drop-down menu offers different options for us to import our data. To import from the Excel workbook, we select the option ‘From File’ and then ‘From Workbook’.
  • Excel opens up a dialog box that helps us navigate and select the workbook.
  • Once we have navigated to the workbook location, we can click on it and then click ‘Open’.
  • This opens up the navigation dialog box. The navigation dialog box gives you a set of data sources.
  • From here, we can select the data on which we want to work.
  • Finally, click on ‘Load’ to import the data.

Become The Highest-Paid Business Analysis Expert

With Business Analyst Master's ProgramExplore Now
Become The Highest-Paid Business Analysis Expert

4. Importing a Multiple Data Source From an Excel Workbook

The following steps will help you import multiple data source from the Excel workbook:

  • Click on the Data tab, followed by Get data command. On clicking this, a drop-down menu opens up. The drop-down menu offers different options for us to import our data. To import from an Excel workbook, we select the option ‘From File’ and then ‘From Workbook’.
  • Excel opens up a dialog box that helps us navigate and select the workbook.
  • Once we have navigated to the workbook location, we can click on it and then click ‘Open’.
  • This opens up the navigation dialog box. The navigation dialog box gives you a set of data sources.
  • In the navigation dialog box, there is an option to ‘Select Multiple Items’. Upon selecting this option, we can choose more than one item.
  • From here, we can select the multiple data sources on which we want to work.
  • Finally, click on Load to import the data.

So, these were a few techniques by which you can import data to Excel. Going ahead, let’s look at a simple demo on how you can Import Data from a CSV file.

A Demo to Get Data From CSV File

We will be explaining how to import data from a CSV file. This process is simple and consists of a few steps.

Importing Data From a CSV File

  • Click on the Data tab, followed by which a Text/CSV file command is found.
  • Once we have selected the “Text/CSV file” option, an ‘Import data’ dialog box is opened.

getData_csv_PowerQuery

  • Select the desired CSV file and click on import. 

getData_csv_2

  • A dialog box named after the CSV file is opened. It shows a preview of the data contained.
  • Finally, click on ‘Load’ to import the data.

getData_csv_3

As you can notice, 14 rows are loaded onto the Excel sheet.

getData_csv_4

Now, let’s move forward and understand various tasks and transformations that can be performed using Power Query. 

Become The Highest-Paid Business Analysis Expert

With Business Analyst Master's ProgramExplore Now
Become The Highest-Paid Business Analysis Expert

What Basic Transformations Can You Perform Using Power Query?

In this section, let’s look at various transformation functions that can be performed easily with the help of a few mouse clicks.

1. Text Formatting Functions

In this section, you will learn how to format text in Uppercase, Lowercase, and understand how to use the Trim operation.

UPPERCASE

Step 1: Load the required data onto the Power Query Editor. This can be done by selecting the respective data source from the Get & Transform Data section of the Excel Data tab. This will open up the Editor, which allows us to edit the data.

Step 2: Click on the column name and then go to the “Transform” tab, which will display a variety of options. Clicking on the option to Format text will open up a drop-down menu with a text edit option of ‘UPPERCASE’.

text_function_1_PowerQuery.

Step 3: Finally, on selecting the UPPERCASE edit option, all the text in the given column will be converted to uppercase.

text_function_2

LOWERCASE

Step 1: Load the required data onto the Power Query Editor. This can be done by selecting the respective data source from the Get & Transform Data section of the Excel data tab. This will open up the Editor, which allows us to edit the data.

Step 2: Click on the column name and then go to the ‘Transform’ tab, which will display a variety of options. Clicking on the option to Format text will open up a drop-down menu with a text edit option of ‘LOWERCASE’.

text_function_3

Step 3: As you can see, all the text from the selected column will be converted to lowercase.

text_function

TRIM

Step 1: Load the required data onto the Power Query Editor. This can be done by selecting the respective data source from the Get & Transform Data section of the Excel data tab. This will open up the Power Query Editor, which allows us to edit the data.

Step 2:To remove all the extra white spaces from the data, click on the column name, and then select the ‘Transform’ tab, displaying various options. Clicking on the ‘Format’ option will display a drop-down menu with a text edit option called ‘Trim’.

/text_function_5.

Step 3: Finally, on selecting the Trim edit option, all the extra white spaces in the given column will be removed.

text_function_6

Strategies for Leadership Excellence

Free Webinar | 6 Dec, Wednesday | 7 PM ISTREGISTER NOW!
Strategies for Leadership Excellence

2. Splitting a Column Using Delimiters

Step 1: Load the required data onto the Power Query Editor. This can be done by selecting the respective data source from the Get & Transform Data section of the Excel data tab. This will open up the Editor, which allows us to edit the data.

Step 2: To split the column with the help of a delimiter from the data, click on the ‘Transform’ tab followed by the ‘Split column’ option. This will display a drop-down menu with an option to split the data By Delimiter.

/splitting_columns_1

Step 3: A dialog box appears where you can select a delimiter. Then click on OK.

splitting_columns_3

Step 4: Now, we can see that the data is split into two columns concerning the delimiter.

splitting_columns_2

3. Transpose a Data Table

Step 1: Load the required data onto the Power Query Editor. This can be done by selecting the respective data source from the Get & Transform Data section of the Excel data tab. This will open up the Editor, which allows us to edit the data.

Step 2: Since we want to rotate the rows to columns, we have to navigate to the Transform tab. Upon selecting, it will show us an option to Transpose the data.

transpose_1_PowerQuery

Step 3: On clicking the transpose option, the rows will be converted to columns. To load the changes into a new worksheet, go to the Home tab and click on ‘Close and load’.

transpose_2

4. Removing Duplicates Using Power Query

Step 1: Load the required data onto the Power Query Editor. This can be done by selecting the respective data source from the Get & Transform Data section of the Excel data tab. This will open up the Editor, which allows us to edit the data.

Look at the duplicate data highlighted in the image below.

remove_duplicates_2

Step 2: Now, we need to navigate to the Home tab → Remove rows option, which will open up a drop-down menu. Click on the ‘Remove Duplicates’ option. 

remove_duplicates_1__PowerQuery.



Step 3:  As you can notice, the data is now free from duplicates. To save the updated table without duplicate rows, go to the Home tab and click on ‘Close and Load’. 

/remove_duplicates_3

Combine Queries 

Power Query has two different options that help us combine different datasets. The two options are:

  • Append 
  • Merge

Become The Highest-Paid Business Analysis Expert

With Business Analyst Master's ProgramExplore Now
Become The Highest-Paid Business Analysis Expert

APPEND

In Power Query, the append operation creates a new table by joining all the rows from the first query, followed by all rows from the second query. Follow the steps below to understand how to perform an Append operation.

Step 1:

  •  Firstly, we have to load the data into the Excel workbook. In this demonstration, you will learn how to Append data from a CSV file.
  • This can be done by selecting the Data tab, followed by the ‘Text/CSV File’ command. 
  • Once we have selected the option, an Import Data dialog box opens. Select the desired CSV file and click on import.
  •  A dialog box opens, which shows a preview of the data contained. Clicking on ‘Load’ will enter the data in a new sheet. 
  • Continue this step to add the required data into new sheets.

Step 2: Now, to append the data available on different sheets, we can navigate to the Data Tab. Here we can find an option called Get data, clicking on which will open up a drop-down menu. You will find an option called Combine Queries. On selecting it, you will find the ‘Append’ option.

append_1__PowerQuery.

Step 3: Clicking on ‘Append’ will open up a window with different options where we can choose to append two tables or more than three. Next, we have to select the sheets that have to be appended. When done, we can click on OK.

append_2

Step 4: The Power Query editor opens up, and the data has now been appended. We can click on ‘Close and Load’ to save these changes, which loads the updated data to an Excel spreadsheet.

MERGE

The Merge option is similar to the JOIN function in SQL. Merge is a way of combining two existing queries and creating a new query. 

Step 1:

  • Firstly, we have to load the data into the Excel workbook. In this example, we will demonstrate how to Merge data from a CSV file.
  • This can be done by clicking on the Data tab, followed by the ‘Text/CSV File’ command. 
  • Once we have selected the option, an Import Data dialog box opens. 
  • Select the desired CSV file and click on import. 
  • A dialog box opens, which shows a preview of the data contained. Clicking on ‘Load’ will enter the data in a new sheet. 
  • Continue this step to add all the required datasets to be merged into different sheets.

Become The Highest-Paid Business Analysis Expert

With Business Analyst Master's ProgramExplore Now
Become The Highest-Paid Business Analysis Expert

Step 2: Now, to Merge the data available in different sheets, we have to navigate to the Data tab. Here we can find an option called Get Data. On clicking it, a drop-down menu will be displayed, which has the option to Combine Queries. On selecting this, click on ‘Merge’.

merge_1_PowerQuery

Step 3: A window will be displayed where we can select the sheets that we want to merge. Now, choose the two columns by clicking on the column header based on which we want to connect both the sheets. Then, click on OK.

/merge_2

Step 4: Once that is done, the Power Query editor opens up with a new column in the end that holds the merge result. To save the changes made, we click on “Close and Load”.

Step 5: The merged data is now loaded onto our Excel worksheet. 

This was all about combining the queries using Merge and Append operations. 

Key Pointers

The Queries & Connections Window:

The Queries & Connections window is a central hub in Power Query where you manage and interact with your data queries and connections. It provides a clear overview of all the queries in your workbook, allowing you to navigate, edit, and refresh them easily. Additionally, the window displays the connections to external data sources, enabling you to modify connection properties, update credentials, or create new connections. The Queries & Connections window is a powerful tool for organizing and controlling your data connections and queries in Excel.

Difference Between the Transform and Add Column Tabs:

In Power Query, the Transform and Add Column tabs are two key sections that facilitate data manipulation. The Transform tab offers a wide range of data transformation options, allowing you to perform actions such as filtering rows, sorting data, removing duplicates, and splitting columns. On the other hand, the Add Column tab focuses specifically on adding new calculated columns to your data. It provides access to various functions, operators, and formulas that can be used to create custom columns based on existing data. Understanding the distinction between these two tabs helps you effectively manipulate and enhance your data in Power Query.

The Transform Tab:

The Transform tab in Power Query houses an array of data transformation features. It enables you to perform essential operations like changing data types, replacing values, aggregating data, pivoting columns, and merging queries. This tab also offers advanced transformation capabilities, such as applying conditional logic, invoking custom functions, unpivoting data, and splitting columns based on delimiters. The Transform tab empowers you to cleanse and reshape your data, ensuring it is in the desired format for further analysis.

The File Tab:

The File tab in Power Query provides options for managing queries and connections at the workbook level. From this tab, you can create new queries, import data from external sources, export queries to other workbooks, or load queries from a query repository. Additionally, the File tab allows you to access the Options menu, where you can configure various Power Query settings, such as privacy levels, global query settings, and regional preferences. The File tab serves as a gateway to essential file and configuration-related functionalities in Power Query.

The Home Tab:

The Home tab in Power Query is the central hub for common data manipulation tasks. It offers a set of frequently used operations, including filtering, sorting, grouping, removing columns, and transforming data types. This tab also provides options to manage query settings, such as refreshing queries, viewing query dependencies, and accessing query properties. The Home tab serves as a convenient starting point for most data transformation activities, allowing you to quickly perform common tasks and navigate to other sections of Power Query.

The Add Column Tab:

The Add Column tab in Power Query is dedicated to enhancing your data by creating new calculated columns. It offers a variety of functions, operators, and formulas that you can use to define custom calculations based on existing data. From basic arithmetic operations to advanced text manipulation, date calculations, and conditional logic, the Add Column tab provides a wide range of tools to transform your data and derive additional insights. This tab enables you to extend the capabilities of your data model and tailor it to your specific analysis requirements.

The View Tab:

The View tab in Power Query provides options to customize the visual appearance and layout of the Power Query Editor window. It allows you to change the zoom level, toggle the Formula Bar display, show or hide gridlines, and adjust the column widths. The View tab also offers options to enable or disable the Formula Bar autocomplete feature and configure the display of formula errors. These customization options help improve the overall user experience and make working with Power Query more efficient.

How to Load Data Back to the Worksheet:

After performing the necessary data transformations in Power Query, you can easily load the data back to the worksheet in Excel. In the Power Query Editor window, you have the option to choose how you want to load the data. You can either load the data to a new worksheet or append it to an existing worksheet. Additionally, you can specify the destination range for the loaded data. By selecting the appropriate options, you can seamlessly transfer the transformed data from Power Query back to the worksheet, where you can further analyze and visualize it using Excel's powerful tools and features.

Auto Refresh a Query:

Power Query provides the functionality to automate the refresh of data queries. This feature is especially useful when dealing with dynamic data sources or when you need to keep your data up to date without manual intervention. To enable auto-refresh, you can specify the refresh settings for a query in the Query Properties window. You can choose to refresh the query upon opening the workbook, at regular intervals, or based on specific triggers like workbook changes or data source availability. By setting up auto-refresh, you ensure that your data is always current, eliminating the need to manually refresh the queries each time.

Export Connections:

In Power Query, you have the ability to export connections, which allows you to share or reuse them across multiple workbooks. Exporting connections enables you to package the connection details, including the data source, authentication credentials, and connection settings, into a file that can be imported into another workbook. This feature is particularly valuable when you want to replicate the same connections in different workbooks or when you need to share connections with colleagues or clients. By exporting connections, you simplify the process of establishing data connections and ensure consistency across your data analysis projects.

Conclusion

In this article, you have learned how to load data using Power Query, perform transformations, and output the data back to your Excel worksheet. Using the Power Query tool, you are saving loads of time by performing numerous functions just with the help of a few clicks! 

Whether you are interested in learning the basics of Excel or want to develop more advanced Excel skills, Simplilearn has a Post Graduate Program in Business Analytics Course for you.

If you have any questions for us, please feel free to mention them in the comments section of this Power Query article, and we’ll have our experts answer it for you right away.

FAQs

1. What is an Excel Power Query?

Excel Power Query is a data transformation and preparation tool developed by Microsoft. It allows users to extract, transform, and load data from various sources into Excel or Power BI using a visual interface. It is a powerful tool for data preparation and analysis tasks.

2. How do you get Power Query in Excel?

Power Query is built into Excel 2016 and later versions but may need to be activated sometimes. To activate it, users can go to the "File" menu, select "Options," and then choose "Add-ins." They can then select "COM Add-ins" and enable "Microsoft Power Query for Excel."

3. Is Power Query free with Excel?

Yes, Power Query is a free add-in for Excel 2016 and later versions and is also available as a built-in feature in Excel for Microsoft 365. It can be downloaded and installed for free on older versions of Excel.

4. What are the basics of Power Query?

The basics of Power Query involve importing, transforming, and combining data from various sources in Excel, allowing users to clean, reshape, and analyze data without complex formulas.

5. What is Power Query Excel used for?

Power Query in Excel is used for importing, transforming, and cleaning data from multiple sources, enabling users to perform advanced data analysis and create unified views of their data.

6. How do you create a Power Query in Excel?

To create a Power Query in Excel, go to the Data tab, click on the Get Data button, select the data source, specify import options, apply transformations in the Power Query Editor, and load the data back to the worksheet.

7. What are the benefits of Power Query?

The benefits of Power Query include streamlined data preparation, automated data refresh, easy data transformation, support for various data sources, improved data analysis capabilities, and the ability to repeat and modify data transformations with a single click.

Data Science & Business Analytics Courses Duration and Fees

Data Science & Business Analytics programs typically range from a few weeks to several months, with fees varying based on program and institution.

Program NameDurationFees
Caltech Post Graduate Program in Data Science

Cohort Starts: 2 Apr, 2024

11 Months$ 4,500
Post Graduate Program in Data Science

Cohort Starts: 15 Apr, 2024

11 Months$ 4,199
Post Graduate Program in Data Analytics

Cohort Starts: 15 Apr, 2024

8 Months$ 3,749
Applied AI & Data Science

Cohort Starts: 16 Apr, 2024

3 Months$ 2,624
Data Analytics Bootcamp

Cohort Starts: 24 Jun, 2024

6 Months$ 8,500
Data Scientist11 Months$ 1,449
Data Analyst11 Months$ 1,449