What Is Power Query?

Written by Coursera Staff • Updated on

Power Query is a valuable data processing tool. Learn more about its benefits when used with Excel, how Power Query and Power BI differ from each other, and about the careers that use Power Query.

[Featured Image] A man works on his laptop in his home office using Power Query to manipulate data.

Data professionals collect, sort, process, and analyze immense data sets, a process made more straightforward when using Power Query in Excel, a tool that can make your job easier. Its design helps to gather and clean data for use within Excel. You can program Power Query with a set of rules (query) for how it will sort your data; fortunately, you only need to establish these parameters once.

This tool offers value for data professionals, and if you are considering working in the data field, Power Query, which is a part of the Power BI suite, will likely be an essential part of your skill set. Finally, pursuing a job in the data analytics realm could prove to be an excellent choice because the US Bureau of Labor Statistics (BLS) predicts employment in this field will grow 23 percent from 2022 to 2032 [1].

Explore Power Query in more detail, including its benefits for users working with Excel, the difference between Power Query and Power BI, and the different careers you might pursue after becoming familiar with it.

What is the difference between Power Query and Power BI?

The main difference between Power Query and Power BI is that Power Query is a tool you can use to clean and shape data. At the same time, Power BI is an interface that allows for more robust visualizations than Excel alone can. You can use Power Query to gather, clean, and import data into Excel. Power Query will also enable you to automate, without coding, the sorting process so that you don’t have to spend time or effort manually inputting the same requests every time you upload data. This valuable tool also lets you gather data from a wide range of sources, such as databases like SQL and Oracle, and prep that information for Excel without the need to convert the different file types yourself.

On the other hand, Power BI, another tool in the Microsoft Power Platform, takes the data you processed in Power Query and turns it into visually engaging graphics and charts. Power BI connects to Excel and Power Query and allows you to design shareable visuals with which other team members can interact.

What is the difference between Power Query and Power Pivot?

Like Power Query, Power Pivot is a data modeling tool that allows you to establish relationships, create complex calculations, and derive insights from data sets. Power Pivot’s design means it has the ability to work with immense data sets. These two data processing tools work together as a seamless pair. Power Query is the best choice for importing your data. Power Pivot takes that data and analyzes it using different complex algorithms and analytical processes to build models of the information.

Benefits of Power Query

The benefits of Power Query vary, including automation and preserving data in its original form. First, Power Query’s ability to automate specific, unique import settings saves you time since you won’t have to manually input those same settings whenever you want to use them. The time saved often translates to money saved, as well, since you’ll be able to take that time otherwise spent on manual inputting and use it more efficiently for other tasks.

Another benefit of Power Query is that it doesn’t write over the files it imports. Instead, the query you establish only reads them for processing, which means the process preserves the data in its original state, allowing you to return to it however many times you need.

Finally, Power Query’s ability to automate your desired settings means that importing the data is much more accurate than if you were to do it yourself since humans are prone to error.

Where to learn Power Query

You can find opportunities to learn Power Query in many different places, including self-learning options and formal courses. One avenue for learning is online tutorials, which take you through the steps of using Power Query. Online courses that teach you the basics of using Power Query are another option and often allow you to pace yourself according to your learning preferences. Degrees and certifications are also an excellent option to develop your skill set, especially if you want to pursue a career in data analytics or computer technology.

Jobs that use Power Query

Jobs in the data industry that use Power Query vary widely across different fields. The following offers several examples to help you find one that fits your interests.

Project accountant

Average annual base salary: $75,905 [2]

Requirements: Bachelor’s degree in a financial field; experience using Excel, project management skills, and a strong understanding of billing protocol

As a project accountant, you would oversee different business projects and make sure the project meets the business’s financial goals and budgets. Typically, this position requires your involvement in every project step, making recommendations, approving spending, sending invoices, and keeping track of incoming payments. In addition to these, project accountants are usually responsible for compiling financial reports and making sure to prepare all required tax documents.

Data analyst

Average annual base salary: $75,227 [3]

Requirements: Bachelor’s degree in finance, computer science, mathematics, or a similar field; many employers might expect you to complete on-the-job training concerning their specific needs and software; some data analysts also pursue certification

As a data analyst, you would typically process, analyze, and report on immense data sets. You might be involved in promoting various business goals and interests, such as maximizing profit, increasing employee retention, and streamlining processes to help meet stated metrics. As a data analyst, you will need to have the ability to take complex, vast data sets and interpret the information into easily understandable reports that provide insight and actionable recommendations using various analysis tools and software programs.

Program specialist

Average annual base salary: $67,514 [4]

Requirements: Bachelor’s degree, often in business management; some employers require a master’s degree or experience within the specific field in which you’ll be overseeing projects

If you choose a career as a program specialist, you could work collaboratively on a team to plan, implement, and manage different programs within a business to ensure that each program successfully meets specific goals and metrics. Typically, program specialists oversee the coordination of multiple projects as they relate to higher-level goals and strategies. In this role, you will likely communicate with other professionals to keep everyone on task, budget, and time.

Getting started with Coursera

Power Query offers powerful benefits for anyone working with data, particularly when used in tandem with Power BI and Power Pivot for a thorough solution for business intelligence and data analysis. Sharpen your Power Query skills and learn about the foundational knowledge required to begin a career in data science with courses and Professional Certificates on Coursera.

With course options such as Macquarie University’s Excel Power Tools for Data Analysis, you’ll learn about the skills needed to succeed in a data science role. You can also go a step further with a program like Microsoft’s Power BI Data Analyst Professional Certificate, which can help you gain experience working with Power Query, Power BI, and SQL. 

Article sources


US Bureau of Labor Statistics. “Operations Research Analysts, https://www.bls.gov/ooh/math/operations-research-analysts.htm.” Accessed March 15, 2024.

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