What is a Power Query?

Power Query is a user-friendly business intelligence tool offered by Microsoft since 2010. Offered as an integrated tool along with MS Excel, this tool is the dream savior of a hardcore data professional. Power Query comes in handy when importing data from different sources and then sorting it into a comprehensible output, preferably in an excel sheet.

The tool was initially offered as free ad-in software in MS Office versions. However, since the 2016 version, Power Query is being offered fully integrated with the excel tool. This in turn, has led to an increase in the usage of this tool to make sophisticated outcomes of messy data sets. Many professionals have even started pursuing power query courses like the Power BI course to better equip themselves with the skills required to operate it.

Note: While using MS Excel, you won’t find “Power Query” written anywhere. Microsoft has provided this service under the heading “Get & Transform Data.”

As per the Market Research Report surveys, the industry focusing on Business Intelligence growth and Power Query has been increasing at a Cumulative Annual Growth Rate (CAGR) of 7.6%. The market size is expected to cross the $30 billion mark by 2025. As a result, not just limited to a skill, Power Query is also emerging as a profession lately.

Power Query: Key Details

Power Query acts as a tool that helps fetch the data, analyze it, and organize it into sorted structures. It is one single solution for Extracting, Transforming, and Loading (ETL) the data.

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The tool comes with a user-friendly graphical interface, which helps in saving a lot of time (almost 80% of total time), which is otherwise wasted on just understanding and sorting data into different sets.

One key advantage of using Power Query is that you do not need to perform filtering functions on data again and again. Once you have made your query, you need to refresh it instead of writing the same code to run other actions. Power Query can be combined with other popular functions like VLOOKUP, which does the final remaining tasks. The scripting language used in Power Query to perform transformations in data is known as M.

At present, you can use Power Query in 2 different experiences.

1. Power Query for Desktop: This is an offline version of the tool used with MS Excel and MS Power BI Desktop.
2. Power Query Online: This version is used in Azure dataflows, Power BI dataflows, and other online and cloud platforms.

For beginners in Power Query, a major confusing question is the difference between Power Query, Power Pivot, and Power BI. The section below helps in solving this doubt.

Power Query vs. Power Pivot vs. Power BI

Power Query is a tool offered by Microsoft integrated with the MS Excel software. The primary function of this tool is to import data, clean it and finally shape it into a structured set.

Power Pivot is an advanced version of Power Query which helps in performing more complicated functions. Power Pivot is useful when you are working with huge data sets.

Power BI is an entirely different tool from MS Excel. It is a separate software that offers better data visualization features than Excel and other advanced options like creating dashboards. Power BI also makes use of both Power Query and Power Pivot to import data and organize it.

How Does Power Query Work?

Power Query works chiefly on four principles: (i) Connect, (ii) Transform, (iii) Combine, and (iv) Load. Significant details regarding these 4 phases of a particular Power Query are given below.

Connect

The first step is to connect with all the data sources. Power Query allows you to connect with both Single and Multiple sources of data at one time. These sources can be anything ranging from local files, local servers, web pages, databases, Azure, and even excel files themselves.

Once the connection is made, the data can be imported, and further stages of transformation can be applied.

Transform

Once the data is imported, the next step is to shape the data according to your requirements, and that is where Transform comes into picture.

Transforming data refers to functions like Removing a Table, Deleting a Column or Row, Merging 2 Sections, Changing the Data Type, Filtering Rows, etc. It helps you get rid of unnecessary information and thus shape the data to analyze only those things that matter.

Power Query tool offers a dedicated section for Transform functions by the name of “Power Query Editor”. It keeps a track of all the transform functions which you have performed. The user interface provides a lot of functions that you can use. In addition to that, you can also go to the Advanced Editor and write your code in M language to perform the transform you want.

Note: These transformations do not make any change in the original data source.

Combine

Power Query and Power Pivot tools are primarily used when there are substantial data sets and multiple data sources. Thus, performing a transform function on just 1 set is not enough, and you also need to combine different sets to get to the outcome.

The Combine phase of Power Query allows you to perform two functions, namely “Append” and “Merge.”

• Append

An append function creates a new query, containing lines of 1st query followed by lines of 2nd query. It is further divided into two types: Intermediate Append and Inline Append. Intermediate Append creates a new query every time, while Inline Append creates appended query once and keeps adding it until the final outcome.

• Merge

In the case of merge, a new table is created containing all the columns of the 1st query table, plus one more column, which helps navigate towards the 2nd query table.

Load

Load is the final phase which allows you to complete the query and load the outcome data into a model or a worksheet that can be used for future references. The user interface of Power Query in Excel offers you multiple options related to how you want to load the data and how you want to view it.

Knowledge of Power Query and allied tools have been helping professionals very much, especially in job roles like Data Scientist, Data Analyst, and BI Engineer. The average salary in such professions ranges from ₹5-9 lakh per annum, depending on the job role. Experienced candidates can go up to earning ₹20 lakh annually.

Whether you are planning to enter the field of data or you are already skilled in analytics, power query is for everyone. So do not delay and join your Power BI/Power Query course now.