Introduction to Power Query Editor
Microsoft Power BI is a Business Intelligence platform that provides an interactive data visualization solution. Power BI is a collection of Microsoft’s cloud-based services, apps, and integrations designed to fuse together different types of data to produce unified, visually appealing, and interactive insights.
Power BI Desktop allows you to connect to data sources worldwide, create appealing and foundational reports, and then share your work with others so they can build upon it and grow their own business intelligence initiatives.
Data from Excel, Power BI, Analysis Services, Dataverse, and other Microsoft applications can be imported into and manipulated with Power Query, a Data Connectivity and Data Preparation Tool.
This post also covers the basics of using Power Query Power BI, including how to connect to data, how to manipulate data, and how to get started.
Power BI, short for “Power BI,” is Microsoft’s proprietary data visualization and business intelligence platform built on the Power Platform.
When it comes to analyzing and reporting on business data, it is one of the most popular tools used by professionals.
Power BI has a wide variety of in-built software services, apps, and connectors that allow for seamless data linking, resulting in Immersive Visuals, Interactive Reports, and Insights.
Data can be compiled, analyzed, visualized, and shared with the help of Power BI.
It is a software-as-a-service platform that may be accessed from a computer, a mobile device, or an internal server.
It is possible to import data directly from the Data Source and see data stored in Databases or Data Warehouses by connecting to a variety of data source connectors in Power BI.
Since Microsoft Power BI can be accessed on any computer, any mobile device, and in the cloud, your teams can gather, manage, and analyze data from anywhere.
Excel, CSV, SQL Server, MySQL databases, PDF, Access, XML, JSON, and many more may all be imported into Power BI.
Power BI’s Essential Functions
Some of Power BI’s most salient characteristics are as follows.
- Hybridization: Power BI provides interfaces with numerous connectors, letting users tap into a plethora of information repositories.
- User Perspective on Modeling Capabilities: Power BI clients can slice and dice massive data models into manageable chunks, design unique diagrams, and pick from a number of alternatives.
- Help from AI: Power BI Data Analytics users can put AI to work for them by utilizing it to clean and normalize data, create Machine Learning models, and rapidly unearth insights hidden in both structured and unstructured datasets.
- Noteworthy Factors: Power BI makes it easier to segment data and apply Data Analytics to it.
- Distribution of Reports: Employees need not be concerned about the confidentiality of company information when sharing reports with coworkers.
In Power BI, what does “Power Query” mean?
Included in both Excel and Power BI, Microsoft’s Power Query is a robust data-processing and analysis tool.
Importing data from Excel tables, CSV files, Database tables, Webpages, and so on is a breeze with Power Query, and you can easily change your data into the correct shape and condition for better analysis.
You won’t have to redo your work with new data once you’ve set up your Power Query methods. With Power Query, you can rapidly establish and automate the same data transformation methods and generate the same data outputs.
Using Power Query in Microsoft Power BI, you may perform complex operations on your data, such as:
- Eliminating blanks, duplicates, and unnecessary data
- Text, numeric, and timeline information conversions
- Both merging and splitting columns are possible.
- Computational columns are being added to the database.
- Summarizing or compiling large amounts of data.
Strengths of Power Query
Some of Power Query’s most significant characteristics are as follows.
- Power Query can import data from a wide range of sources, such as text files, Excel Workbooks, and CSV files, and then export that data in a variety of formats.
- Power Query’s Merge feature is equivalent to Excel’s VLOOKUP command. The latter is a helpful approach to finding matching values, but it runs into some difficulties when used in a massive dataset with thousands of rows.
- In cases where updates to the same source data must be imported at regular intervals, such as once a week or once a month, the task of manually assuring data replication becomes burdensome.
- Power Query was designed so that its use could be achieved with little to no familiarity with computer programming. The interface is intuitive, requiring no more effort than opening Excel and clicking a few buttons to apply filters.
- Actions and procedures are tracked and automated with Power Query. All of these tasks are simplified with Power Query, and the program even keeps track of your actions so you never have to perform them twice. You can save a lot of time if you don’t have to repeatedly prepare the same data (either daily, weekly, or monthly) for analysis.
Power Query Power BI Overview
Power BI is a standalone application that includes Power Query. It offers additional connectivity options than Excel’s Power Query.
It also has enhanced graphics and the ability to publish to the Power BI Service to facilitate the sharing of reports.
In addition, you can get details on connecting to data, influencing data, and getting started. Consider the Power Query Editor.
1) Power Query Editor for Power BI
To open Power Query Editor, select Transform data from the Home tab of Power BI Desktop.
Power Query Editor displays a blank pane when there are no data connections, ready to be populated with data.
When a query is loaded, the Power Query Editor window takes on a more engaging appearance. Connecting to the following online data source causes Power Query Editor to download data that can be manipulated in various ways:
Here is how Power Query Editor appears once a data connection has been established:
- Numerous buttons in the ribbon are now active for interacting with the query data.
- The left pane contains a list of queries that can be selected, inspected, and modified.
- The specified query’s data is shown and formatted in the middle pane.
- The Query Settings pane appears, displaying the query’s properties and applied steps.
Our tour of the interface will begin with the ribbon and proceed through the Queries pane, the Data view, and finally the Query Settings pane.
2) The Query Tab
The Query Tab in the Power Query Editor’s ribbon contains four Tabs such as Home, Transform, Add Column, View, Tools, and Help. On the Home tab, you’ll find the common query tasks.
Select New Source to connect to data and initiate the process of query creation. A menu including the most common data sources is displayed.
The Transform tab provides access to common data transformation operations, including:
- You can add or remove columns.
- Modifying data types
- Column division
- Other duties motivated by data include
The right-click context menu on a column or other piece of data in the main pane provides access to many of the same options as the ribbon.
3) The left-hand Inquiries Pane
The left pane, or Inquiries Pane, indicates the number of current queries as well as the question name.
Selecting a query from the left pane will load the relevant data into the central pane, where you can manipulate it as needed.
This image illustrates the left pane containing a query.
4)The Center Data Pane
The Data Pane, located in the center of the window, displays the results of the active query. Most of the action in the Query view takes place in this pane.
The diagram below displays the Web Data connection that was previously established. By clicking the right mouse button on the Overall score column’s header, you can access the contextual menu.
Many of these right-click options are identical to buttons on the tabs of the ribbon.
Choosing a submenu item via the right-click menu causes the corresponding data step to be applied to the query (or a ribbon button). Additionally, steps are saved as a query parameter. The next section describes the order in which the steps are recorded in the Query Settings window.
5) The Query Settings Pane on the Right in Power BI
The Right Pane, commonly referred to as the Query Settings Pane, displays all query-related steps.
For instance, the Applied Steps section of the Query Settings pane in the accompanying screenshot displays the fact that the type of the Overall score column was just adjusted.
Additional shaping steps are indicated in the Applied Steps section as they are applied to the query.
It is essential to recognize that the core data has not been altered. In contrast, Power Query Editor alters and shapes its perspective on the data.
Power Query Editor not only provides a reshaped and updated view of the underlying data, but it also affects the perspective of any interactions with the data.
In the Query Settings window, you can modify the names, and remove, or rearrange the order of the individual stages.
To accomplish this, right-click the step in the Applied Steps section and then select the desired option from the resulting menu.
When running a query, each step is carried out in the order it appears in the Applied Steps window.
6) Power BI’s Advanced Editor
The Advanced Editor presents the code generated at each stage by the Power Query Editor. Your own custom shaping code, written by you, is possible. To open the advanced editor, select View, then Advanced Editor from the ribbon. A window will open with the current inquiry code on it.
In the Advanced Editor box, code can be modified directly. To dismiss the pop-up, click the corresponding button (Done or Cancel).
7) Saving of Work
When you are satisfied with your query, select Close & Apply from the File menu in the Power Query Editor. This operation saves the modifications and closes the editor.
Power BI Desktop provides a progress dialogue as progress is made.
Power BI Desktop allows you to export your work to a.pbix file when you’re done. To save your work, select File > Save (or File > Save As), as shown in the following figure.
Perks of Using a Power Query Business Intelligence
The following are some of the perks that will hold you captivated for the long haul.
- Right Interface: Power Query comes with a multitude of data connections. TXT, CSV, and Excel files, as well as databases like Microsoft SQL Server, and major SaaS services like Microsoft Dynamics 365 and Salesforce, are all supported as data sources.
- Rapid Filtering: Filtering your data as early as feasible in the query process is usually a good idea. It is also recommended that you eliminate any information that is irrelevant to your investigation. This helps you focus on what needs to be done by only showing relevant information in the data preview section.
- Modular Approach: It is absolutely possible to design a single query that combines all of the essential calculations and transformations. This is something that can be accomplished by using the modular strategy. If there are numerous processes involved, though, it may be best to break the question up into several smaller questions that build off one another.
- Query future-proofing: Power Query’s different features make it possible for your query to continue to run and update even if some parts of your data source are modified.
- Create reusable functions: Creating a Power Query custom function that can be employed quite as many times as necessary could be useful when you need to implement the same set of modifications to multiple queries or data
Power Query, which is included with Microsoft Power BI, is a helpful tool for importing data from a variety of sources.
Power Query is limited to Excel sheets and CSV file formats; however, Power BI allows users to import data from other sources, including databases such as MySQL and PostgreSQL, SaaS platforms such as Mailchimp and Zendesk, and CRMs such as Salesforce and Hubspot.