Starting Report Generation: Power BI Desktop

Starting Report Generation: Power BI Desktop

In this article, we will share the tips of using Power BI Desktop.

This short “Power BI Desktop” tour was created to help you quickly implement effective data models that describe how the application works, show you what it can do, and deliver excellent reports, as well as strengthen your business intelligence initiatives.

Power BI Desktop lets you create a set of queries, data connections, and reports that can be easily shared with others.


“It’s now easier to model, create, share and expand new insights.”

Microsoft Power BI Team

“It’s now easier to model, create, share and expand new insights.”

Microsoft Power BI Team
Power BI Desktop combines proven Microsoft technologies and works seamlessly with the online Power BI service.

Data analysts will recognize that Power BI Desktop is a powerful, flexible and highly accessible tool for connecting and shaping the world of data, creating powerful models, and preparing well-structured reports.

How Power BI Desktop Works

With Power BI Desktop, you can connect to, shape, and generate data using this model.

When the steps (linking, shaping, and reporting) are completed the way you want, you can save this work with the .pbix extension, the Power BI Desktop file format.

Power BI Desktop files can be shared like any other file, but the most interesting way to share Power BI Desktop files is to upload (share) them to the Power BI service.

Power BI Desktop centralizes, simplifies and simplifies the process of designing and creating business intelligence repositories and reports, which is normally a disorganized, disjointed and laborious process.

Ready to try ? Let’s start Then

Installing and Running Power BI Desktop
You can download Power BI Desktop by selecting the gear icon in the Power BI service, then selecting Power BI Desktop.


Power BI Desktop is installed as an application and runs on your desktop.


When you run Power BI Desktop, a Welcome screen appears.


You can Import Data, View Recent Sources, or Open Other Reports using the links in the left pane of the Direct Welcome screen.

If you close the screen (select the x in the upper right corner), the Report view of the Power BI Desktop is displayed.

Power BI Desktop has three views: Report view, Data view, and Relationships view.

Power BI Desktop also includes the Query Editor, which opens in a separate window. You can create and convert queries in the Query Editor, then upload the collapsed data model to Power BI Desktop and generate reports.

The following screen shows three view icons on the left side of Power BI Desktop: top-down Report, Data, and Relationships. The yellow bar on the left indicates the view currently displayed. This example currently displays the Report view.

You can change views by selecting one of these three icons.

Once Power BI Desktop is installed, you’re ready to connect to, shape, and generate reports (usually following this sequence).

In the next few chapters we will examine each one in turn.

Connecting to Data

Once Power BI Desktop is installed, you’re ready to connect to the ever-growing world of data. A wide range of data sources is available in the query window.

The following image shows how to connect to the data by selecting Get Data> Other sonra after selecting the Input Ribbon.


In this quick tour, we’ll connect to several different Web data sources.

Imagine that you’re retiring (you want to live in a sunny, tax-friendly and health-friendly place) or you’re a data analyzer and you need this information to help your customers.

For example, you may also want to help your sunglasses retailer target sales in the most sun-exposed areas.

Here is a web resource for both scenarios with useful data on these issues:

Select Get Data> Web and paste the address.

When you select OK, the Power BI Desktop’s Query function starts. The query establishes a connection with the Web resource, and the Navigator window returns the items it finds on that Web page.

In this example, a table (Table 0) and a generic Web Document are found. We are interested in the table, so we choose the table from the list. The Navigator window displays a preview.

At this point, we can load the table or edit the query before loading the table by selecting Edit at the bottom of the window.

When we select Edit, the Query Editor starts and presents a representative table view.

The Query Settings pane appears. (If not, you can select View from the ribbon and then select Show> Query Settings to display the Query Settings pane.)

It appears as follows.


h2> Shaping and Combining Data
Now that we’re connected to a data source, we’ll need to adjust the data to meet our needs.

Sometimes when we say tuning, we can convert data; in other words, we mean renaming columns or tables, converting text to numbers, removing rows, setting the first row as a title, and so on.

The Query Editor in Power BI Desktop uses plenty of right-click menus, as well as tasks available in the ribbon.

Most of the items that can be selected in the conversion ribbon are also available by selecting one of the options in the menu that appears when you right-click an item (for example, column).

Shaping Data

When you format data in the Query Editor, you provide step-by-step instructions (which Query Editor applies to you) to set up the data that the Query Editor loads and presents.

The original data source is not affected. Only this particular data view is set or shaped.

The steps that you specify (such as renaming a table, converting a data type, or deleting columns) are saved by the Query Editor, and these steps are applied each time that query is connected to the data source.

This way, the data is always shaped as you specify. This happens every time you use the query in Power BI Desktop, or whenever a user uses the query that you share (for example, in the Power BI service).

These steps are saved in the Applied Steps section in the Query Settings pane, respectively.

These steps are saved in the Applied Steps section in the Query Settings pane, respectively.

The following image shows the Query Settings pane for a shaped query. In the next paragraphs we will examine each of these steps.


Let’s go back to our retirement data that we found by connecting to a web data source and shape it to meet our needs.

First of all, most ratings were brought to the Query Editor as an integer, but not all. (One column had both text and numbers, which means the column was not automatically converted). We need to convert the data into numbers.

No problem. To change the data type, just right-click the column header and select Change Type> Integer. If we had to select more than one column, we would first select a column and hold down the SHIFT key, select other adjacent columns, and right-click on a column heading to change all selected columns.

You can also use the CTRL key to select nonadjacent columns.

You can also use the CTRL key to select nonadjacent columns.

You can also change or convert these columns to headings instead of text using the Convert ribbon.

As you can see below, the Data Type button on the Convert ribbon has an arrow that allows you to convert the current data type to another type.


The changes are shown in the Steps Applied section of the Query Settings pane.

If you want to remove any step in the shaping process, just select the X to the left of the step.

To make the query the way we want, we need to make a few more changes:

-Remove the first column: We don’t need this column because it contains unnecessary lines that contain the phrase “Check out how your state ranks for retirement bir.
-Correcting some errors: The text on one of the columns on the web page was mixed with numbers. (Some states were categorized into a category.) This works on the website, but is not suitable for our data analysis. In this example it is easy to fix. It also shows some great features and functions of both the Query Editor and the Steps Applied section
-Changing Table Name: Table 0 is not a useful identifier, but it is easy to change

Each of these steps is illustrated in the Shaping and Consolidating Data article in Power BI Desktop.

Browse this page or continue reviewing this document to see your next steps. The procedures described in the next section are described after the above changes have been applied.

Combining Data

These data on the various states of the states are interesting; it will be useful for creating additional analysis studies and queries. However, there is a problem at this point;

Most of the data shown uses two-letter abbreviations for state codes instead of the state’s full name. We need a method to associate state names with acronyms.

It’s our lucky day! There is another general data source that does exactly this, but we need to do some shaping before we link it to our pension table.

Below is a web resource for state abbreviations:

In the Query Editor, select Get Data> Web on the Home banner, and type the address, and when you select OK, the contents of that Web page are displayed in the Explorer window.

We choose Table [edit] because it shows the data we want, but we’ll need to do some styling to match the data of this table.

Each of these steps is also shown in the Shaping and Consolidating Data article in Power BI Desktop. These steps can be summarized as follows:

We select Edit and then do the following:

-Remove the first two rows: These are the result of the way the table for the Web page was created, and we don’t need those rows.
-Remove the bottom 26 lines: These are regions that we don’t need to add.
-Filtering out Washington: We will not add this data to our list because Washington is not included in the pension statistics table.
-Remove unnecessary columns: We only need to map states to two-letter official abbreviations, so we can remove other columns.
-Using the first line as the title: Since we removed the first three lines, the title we want is the topmost line available.
-It is also important to evaluate how one step may affect the next steps. If you remove a step in Steps Applied, subsequent steps may not show the originally planned behavior because of the effect of the query on the step sequence.
-Rename columns and table: As always, there are several ways to rename a column, and you can choose what you want.

Because the StateCodes table is configured, we can combine these two tables or queries into one.

Since the tables we currently have are the result of the queries we apply to the data, they are often called queries.

There are two basic ways to join queries: merge and insert.

When you want to add one or more columns to another query, you merge the queries.

When you have additional rows of data that you want to include in an existing query, you add the query.

In this example, we want to merge queries.

First, we select the query that we want the other query to merge into, and then select Merge Queries from the Home tab in the ribbon.

The Merge window appears, where we will determine which table we want to merge with the selected table, and then select the matching columns to use for the merge.

In the RetirementStats table (query), select the State option, and then select the StateCodes query. (In this example, it is easy to choose because there are only two queries.

When you connect to many data sources, you will encounter many queries to choose from.) When we select the correct matching columns (the State column in the RetirementStats table and the State Name column in the StateCodes table), the Merge window appears as follows and the OK button becomes active.

At the end of the query, NewColumn, which is the contents of the table (query) that is merged with the existing query, is created.

All columns of the merged query are collapsed to include them in NewColumn, but you can expand the table and include the columns you want by selecting Expand.

Select the expand icon () to expand the merged table and select which columns to include. The Expand window appears.

In this example, since we only want the State Code column, we select only this column, and then select OK.

We don’t need or use the original column name as the prefix setting, so we clear the corresponding checkbox.

If you leave this check box selected, the merged column is called NewColumn.State Code (the original column name or NewColumn, a period, and the name of the column passed to the query).

We have obtained a single query (table) that combines two data sources, each of which is tailored to our needs.

This query can form the basis for many other interesting data connections, such as housing cost statistics, demographic information, or business opportunities in any state.

For now, we have enough data to produce a few interesting reports, all in Power BI Desktop.

Since this is a milestone, let’s save this Power BI Desktop file and name it Getting Started with Power BI Desktop.

Select Close & Apply on the Home tab to apply the changes in the Query Editor and upload them to Power BI Desktop.

Creating Reports

After the table is loaded, you can make additional changes and reload the model to apply the changes you made.

But for now, that’s enough. You can start generating reports in the Power BI Desktop Report view.

Report view has five main fields:

-Ribbon displaying frequently used tasks associated with reports and visualizations
-Report view or canvas where visualizations are created and edited
The Pages tab at the bottom, which allows you to select or add a report page
-Visualizations pane where you can change visualizations, customize colors or axes, apply filters, drag areas, and more
-Fields pane where query items and filters can be dragged to Report view or to the Filters area of ​​the Visualizations pane.

The Visualizations and Areas panes can be collapsed by selecting the small arrow on the side to provide more space in the Report view to create engaging visualizations.

You can see these arrows pointing up or down when changing visualizations.

This indicates that you can expand and collapse the section appropriately.

To create a visualization, simply drag an area in the Fields pane to Report view.

In this example, drag the State field in the RetirementStats section to see what happens.

Take a look at this: Power BI Desktop automatically created a map-based visualization because it determines that geographic location data is available in the State area.

Note that we can select different types of visualization in the Visualizations pane and drag fields to other regions to apply a Description in the region below these icons or to change the visualization in another way.

Let’s go a little further and see how the Report view looks after adding a few visualizations, as well as new Report pages.

The first Report page provides a perspective on the data based on the Overall rank column.

When you select one of the visualizations, the Fields and Filters pane shows which fields are selected and the structure of the visualization (which fields are applied to the Shared Axis, Column Values, and Line Values).

This Report contains six Pages that visualize specific elements of your data.

-On the first page above, all states are shown based on the Overall rank column.
-The second page focuses on the top ten states based on the Overall rank column.
-For the third page, the top 10 states (and associated data) in terms of cost of living are visualized.
-The fourth page focuses on the weather and the 15 most sunny states are filtered.
-On page five, the Community well-being column for the first 15 states was graphed and visualized.
-Finally, crime statistics are visualized and the ten best (ie worst) states are shown.
-Cost-oriented report page looks like the following.

You can create various interesting reports and visualizations.

Share Your Work

Now that we have an almost completed Power BI Desktop report, we can share the report with others in the Power BI service.

There are several ways to share your work in Power BI Desktop.

You can publish your work directly to the Power BI service, upload the .pbix file directly to the Power BI service, or save the .pbix file and send it like any other file.

First, let’s look at the option to publish to the Power BI service directly from Power BI Desktop. Select Publish on the input strip.

You may be prompted to sign in to Power BI.


After you sign in and publish is complete, you will see the following dialog box.

When you sign in to Power BI, you’ll see the Power BI Desktop file you’ve uploaded in the Dashboards, Reports, and Datasets sections of the service.

Another way to share your work is to upload it from within the Power BI service. You can turn on the Power BI service in a browser using the following link:

I https://app.powerbi.co
Select Get Data to start the installation of your Power BI Desktop report.

The Get Data page appears, where you can choose where to retrieve your data. In this example, we select the Import option in the Files box.

The Files view appears. Here we select Local File.

The file you select is installed by Power BI.

After the file is uploaded, you can select the file in the Reports section in the left pane of the Power BI service.

The Power BI service displays the first page of the report. You can select any tab at the bottom of the page to display the desired page of the report.

You can modify a report in the Power BI service by selecting Edit Report at the top of the report canvas.

To save your report, select File> Save As in the service. Using your report in Power BI, you can create many interesting visuals and pin these visuals to dashboards.

After saving the report, select the Share icon on the main page.

Here, you can send an email to colleagues with whom you want to share the clipboard.

You can create a variety of interesting compilations and visualizations of data using Power BI Desktop and Power BI service.

  • I couldn’t resist commenting. Well written!

    31 May 2020
  • Useful information. Fortunate me I found your site by accident, and I
    am surprised why this accident did not came about
    in advance! I bookmarked it.

    31 May 2020
  • It’s not my first time to go to see this web page, i am browsing this site dailly
    and get fastidious data from here everyday.

    4 June 2020
  • This design is spectacular! You obviously know how to keep
    a reader amused. Between your wit and your videos, I was almost moved to start my own blog (well, almost…HaHa!) Fantastic
    job. I really loved what you had to say, and more than that,
    how you presented it. Too cool!

    24 June 2020