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First Interaction with Power BI Desktop:

Power BI is an awesome visualization tool that helps in getting data from various data sources, cleaning the raw and dirty data, creating relationships between data models, and displaying the data into amazing visualizations.

When you first open Power BI Desktop, a window pops up.

This is the welcome screen. You can access Recent Data sources, Get Data icon, Power BI Blogs, Tutorials, Forums, etc. from here.

Power BI Desktop: On the top left side of the screen, there is a small rectangle which is a save button. It looks like this:

Below are Re-do and Un-do Buttons.

This is the main ribbon on the Desktop.

These are explained under:


When you click on File menu, you will be able to see the below options:

New: This opens a new Power BI window which allows us to start a new Project.

Save and Save As: It allows us to save the current work as PBIX file in our local machine. Whereas ‘Save’ button saves the change we made in already existing file, ‘Save As’ creates a new PBIX file or saves the existing file to a new location.

Get Data: This button allows us to import Data from various sources. The list of Data sources to which Power BI can connect to, is huge.

Import: It allows us to import Power BI template, Power BI visual from file and AppSource.

Export: It allows us to export Power BI template and Export to PDF

Publish: This allows us to publish the report to Power, which is a cloud-based service.

Options and Settings:



Data Load: It allows us to control the settings while loading the data into Power BI Desktop such as Type Detection, time intelligence and background data.

Power Query Editor: We can deal with settings of Power Query Editor with this tab such as enabling/ disabling intellisense of M language.

Direct Query: It gives the option to control Direct Query from SAP Hana Database.

R Scripting: This gives the options to choose the Integrated Development Environment (IDE) of R to launch in Power BI Desktop and the location to store R script in local machine. R script is used to prepare data models and to create reports in Power BI, after a connection is established between R and Power BI Desktop.

Python Scripting: This gives the options to choose the Integrated Development Environment (IDE) of Python to launch in Power BI Desktop and the location to store Python in local machine. Python is used in Power BI for data cleaning and other transformations. Python is used for creating visualizations as well.

Security: This gives security options for Data extensions, custom visuals, authentication browser and a few other things.

Privacy: This gives the option to combine data according to privacy level settings for each source or each file or ignore the privacy level settings.

Regional Settings: It controls settings for Application and Model language.

Updates: This allows to enable/ disable update notifications of Power BI Desktop.

Usage Data: If enabled, information is collected about how the Power BI Desktop is used.

Diagnostics: This feature, when started, runs evaluations caused by the user. ‘Diagnose step’ runs an evaluation of a single step that the user is trying to investigate.

Preview Features: This gives a list of features in the latest version of Power BI Desktop to enable/disable.

Auto Recovery: When anyone creates a Power BI Model, a copy of this file is saved in Auto Recovery and the file can be accessed from the auto recovery file location, if the file is closed without saving.

Report Settings: This provides settings for visuals, accessibility, page alignment and Format pane in the canvas area of the report page.

Current File:

Data Load: It controls the settings of how the data will look like when imported, such as detection of column types and headers, auto detect relationships, parallel loading of tables, etc.

Regional Settings: It controls language settings for text of current file.

Privacy: It gives control for privacy for each data source to the user. The user has the option to combine data according to privacy level for each source or to ignore the privacy level for source data. There are three types of Privacy levels in Power BI- Organizational, Public and Private.

Auto Recovery: Enable/ disable auto recovery of current files.

Published Data Set: It gives control to the end user to edit SAP variables in Power BI Premium and shared workspaces. It can only be used with direct query connections.

Query Reduction: It gives control on number of queries by disabling cross highlight/ cross filter, control on slicers and filters .

Report Settings: This gives the option to enable/disable personalized visuals, export data settings, etc.

Data Source Settings:

Get Started: This button opens the startup Power BI welcome screen.


This allows us to bring Data from various sources like Excel workbooks, Power BI Datasets, Dataflows, Dataverse, SQL Server, Text files, etc. Selected sheets will be available as ‘Table Query Objects’ in Power BI.

This allows you to select Excel worksheets to bring into Power BI Desktop. The selected sheets become table query objects in Power BI.

Data Hub Items:

Power BI Datasets: You can use Power BI datasets in your organization for which you have build permission / Read only permissions, with this tab. Read only permissions have limited access to the user.

DataMart (Preview): Data marts are web-based, built in visuals which integrates with Power BI and is used for self-service data analytics. Data marts are available for premium or Premium Per User (PPU) licenses. One single Data Mart can contain multiple data sources.

It allows you to connect to SQL Server Database and bring the required data into Power BI Desktop. The imported tables become Table Query Objects.

It allows you to create a new Table inside Power BI. This table is loaded as a Table Query object inside Power BI Desktop to perform further calculations/ visualizations.

It allows you to connect to Dataverse Environment domain by copying and pasting the URL of Environment Domain. The data connectivity can be Import or Direct. To get to that environment, go to From there, you will get the list of all the environments you are working in. You can select the domain name, by clicking the environment you want to connect with, copy the URL of that domain and paste it in Power BI Desktop Dataverse window.

This will list out all the recent sources from where you have extracted the data. You can bring in additional data in Power BI desktop from recent sources.

If you click on table like structure on top of this button, it will open Power Query Editor window, which helps in cleaning, and perform further calculations with the help of M language.

If you click on drop down in this button, it will give you two options:

1. Transform data- Go to Power Query Editor Window as defined earlier.

2. Data Source Settings- Allows you to change the source data in your local machine if there is a change in the location of the source file.

This updates the Table Query object if there are changes in source data.

Visualization Pane:

This Pane allows you to select the visual you want to display your data in. It contains Bar charts, Column charts, Line charts, Area charts, Slicer visual, Pie chart, Donut chart, Treemap visual, etc. From the dropdown, you can also import custom visuals from local machine as well as from the web.

This creates a text box inside the canvas area, to provide headings, subheadings, etc. along with the visuals.

As the name suggests, it allows you to import more visuals from your local machine or AppSource, if you want to display the data in other than already provided visuals.

When you click on this button, a dialogue box will open. This allows you to perform calculations based on the needs of the model for reports. For example, if net price and unit cost is given in the table, we can calculate the amount of sales by using the values of these columns. The created measures can be used in the report to display the calculated measure value. The language used in calculating ‘New Measure’ is DAX (Data Analysis Expressions). The new measure is displayed as an explicit measure with a calculator symbol in the list of columns, under the table for which this measure is created. The new measure dialogue box can also be opened when we right click on Table Query Objects on the right side of the Power BI Desktop in Report view.

Quick measures are for people who are not very comfortable in writing DAX queries, especially the beginners. If enabled, it gives the option to calculate the required value easily. The user can specify necessary values for calculating the new value and Power BI takes care of writing DAX for you. The DAX generated behind the scenes can be looked at by clicking the new measure created under the table.

Sensitivity labels can be applied in Power BI Desktop (Reports) and Power BI Service (Datasets, Dataflows, Reports and Dashboards,). The sensitivity labels must be enabled for tenant to use. Admin can define the users who can apply sensitivity labels. Only Pro or Premium per user licensed people, who are a part of the security group, can apply a sensitivity label.

This allows you to publish the report in Power BI service, which is a cloud-based service and is a part of Power BI Suite.


This allows you to add a blank page or make a duplicate of the existing page in your report. Both actions can also be performed by clicking on the plus sign and Right-clicking on page names simultaneously, under the canvas area.

This opens a window inside the canvas area from which you can select the type of visuals you want to display your data in.

Already explained under HOME.

When you click on this button, a window pops up in the canvas area which allows you to build a visual based on the values you provide. Q&A can be set up by the report developer, by going to settings of Q&A to add more synonyms, so this feature can respond better to people’s questions.

This visual is used if you want to analyze the important factors which are behind a particular metric. For example, which products bring in the highest level of sales, which characteristics in a teacher motivate a student to learn more, etc. Key influencers visual has AI features enabled.

It is a type of visual which also analyzes a particular metric with respect to its influences based on the other factors. For Example, we can analyze company sales with respect to its influences by category and location. It gives us step by step analysis of a particular value.

If enabled, this gives you a written text highlighting the important points in a report/ visual. It has some limitations such as cross filtering. It cannot be connected live with the SQL server Analysis Services (SSAS) and Azure Analysis Services. Also, it cannot be pinned to a dashboard. There are a few other limitations as well.

This feature allows you to insert paginated reports from Power BI service (Pro or Premium Per User capacity) in your Desktop Report. The paginated report is seen as a separate visual in canvas area. The Paginated Report visual doesn’t interact with the other visuals in the desktop if there are no parameters defined in the Paginated Report and vice versa. In other words, Paginated Report brought in the Power BI Desktop can be both static and dynamic, depending on the parameters.

Power Apps can be integrated with Power BI. We can load the data from Share Point Online List by providing the URL for our Dataset. We can create visualizations based on that dataset and must specify the fields of the dataset in the Power App window. It also gives the option for creating a new App, if not created before. The reason to integrate Power BI to Power Apps is, if some changes happen in our source data, we can update the Power App of that Dataset, and after clicking Refresh button in Power BI Desktop, the report will automatically be refreshed.

This provides you with the ability to automatically refresh Power Bi Datasets. You will get a Power Automate visual in canvas area by clicking on this tab, through which an automatic flow in the report can be created. Automation can be triggered by a condition/ action. For example: if sales have reached a particular point, the team, as defined in the automation process, will receive an email accordingly.

We can use this text box to write our headings for the visuals in canvas area.

Buttons are created to switch quickly from one visual to another in the Report page. We must create actions for buttons to make them work. We should press Ctrl+ click on button for it to switch between different visuals. We can perform Back, Bookmark, Drill Through, Page Navigation, Web URL, etc. through buttons.

This is used to insert different shapes in the background of text box, and we can customize the shape with basic formatting options.

This is used to insert an image saved from your local P.C. into report page.

Sparklines are like lines in line charts which can be added to a spreadsheet, for example table visual and Excel spreadsheet. They are shown in a separate column in a matrix or table visual which shows the trend of a particular field. They have little details as compared to line charts, which are visuals on their own.


This tab allows us to create new relationships, auto detect relationships, edit the type of relationship (Active, inactive, single/ Bidirectional) and delete relationships between data models.

New column/ Calculated column is not present in the original data model but is added at the design time. The new column is added to the Power BI data model and can be used in visualizations. Calculated columns operate on a row-by-row basis. The language used at the model level to add new column is DAX.

This tab is used to create a new table, in addition to existing imported tables, within Power BI and can be used in various calculations and visualizations.

This feature is enabled in Direct Query mode and Mixed mode (Direct Query) part. It allows us to refresh the data when there are any changes in the source database. It is also known as ‘Automatic Page Refresh’. It allows two types of refreshes- Fixed Interval and Change Detection. Change Detection can be enabled for one measure as well.

This option, when enabled, allows us to create parameters, so end users can change the parameter value and see the reports based on those changes. Parameter accepts the value on the fly i.e., at run-time. There are two types of parameters under Modeling tab – Field parameter and Numeric Range. Field parameters gives the choice of looking at a particular measure with respect to the chosen field, whereas Numeric Range parameters allows to filter the data based on range of numbers and dates.

‘Manage Roles’ gives the option to enable ‘Row Level Security (RLS)’ in Power BI, so users can view the data based on the specific roles they are in. We can create dynamic RLS by using the DAX function USERNAME() or USERPRINCIPALNAME(). An Excel table, which contains the usernames/ User IDs should be in the Data Model and proper relationships should be configured.

‘View As’ tab is provided to view the roles created under ‘Manage Roles’ to check whether the RLS is working properly for the end user of the report.

This tab allows us to set up Q&A feature for end users, so that they can ask questions according to their requirements.

This allows us to change the language of Power BI Desktop according to user’s requirements. As of now, Power BI supports more than 40 languages, but few features are available in English only.

This allows us to define terms and phrases that are understood by Power BI Q&A feature when a user asks question for a dataset. Power BI creates a linguistic schema automatically when you import a dataset. These schemas are saved in the form of .yaml files. We can change linguistic schema exported from Power BI Desktop, by adding phrases that are understood by consumers. Basically, linguistic schemas create relationships between how people can ask questions about the dataset and how Power BI reacts.


This allows you to customize the Power BI Report. Besides the in-built themes, we can also import other themes from the web. The imported theme is saved as a JSON file in the local machine and can be used in the report. When you apply a particular theme, all available visuals in the report use the same colors.

This gives three options for the canvas area- ‘Fit to Page’, ‘Fit to width’ and ‘Actual size’. This is self-explanatory.

As the name suggests, this tab allows us to design report page which can be easily viewed on the mobile. This doesn’t affect how the visuals look in Desktop.

Gridlines, when turned on, help in aligning the visuals, for a better look.

Snap to Grid feature automatically aligns the visual to the nearest axis, when moved or resized in the canvas area.

The above options, when turned on, display the Filters pane, Data pane and Format pane, on the right side of the Desktop. Through filters pane, various filters (Page level and Report Level) can be added in the canvas area. The data pane displays various tables and calculated fields. Format panes give the options to make the Report/visuals look better by changing background, transparency, adding text, etc.

Bookmarks are added to the Report to give control to the user to move from current page to bookmarked page. We can capture a particular state of the report and add it to the bookmark for easy access.

The selection pane gives the option to specify whether the added objects in the report should be visible or not.

Performance Analyzer can be used to interact with the report and see how much time each visual is taking to load and DAX query is taking to give the results. This is done to improve the Performance of the Report. Time recorded is in milliseconds.

This tab can be used to synchronize various slicer visuals with each other, which means if we filter a particular state in a slicer, other slicers, which are synched with this slicer, will automatically get updated.


This is mostly used for Direct Queries. ‘Pause Visuals’ allows to stop refreshing the visual while you want to add new field to the visual on the canvas area. You can click on ‘Refresh visual’ to bring the visuals back to Refreshing state.

There are three options under this:

1. Query Reduction- This adds an apply button to the filters pane and cross-filtering and cross-highlighting between visuals is turned off. This is basically used for Direct Query connection.

2. Interactivity- This does the opposite of Query Reduction, that means, it turns on the cross-filtering, cross-highlighting and real time changes between visuals. This is good for Import Queries.

3. Customize- It gives the option to customize Query Reduction, to apply slicer/filter changes instantly or to add apply button to all basic filters/ slicer or add a single apply button to the filters pane to apply changes at once or to reduce number of queries by disabling cross filtering/cross highlighting.

It allows you to make selections from all slicers at once for Query Reduction.


External Tools:

Some external (third party) tools such as Power BI Helper, DAX Studio, Tabular Editor, etc. can also be installed in Power BI Desktop which helps us in optimizing the report and use features within Power BI Desktop which are not in-built.

Thank you!

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