The below article goes through various functions of data visualization using Power BI.
Did you know that around 90% of the entire world’s data has been created alone in the last few years? Don’t get baffled by this humongous volume of data, it is not complicated. Simply said, organizations across industries want to collect their user’s interactions with the products or services so that they can make relevant business decisions and strategies which will lead them to their intended goal.
Here comes data visualization to the rescue. In business intelligence, visualization is helping today’s rapidly changing economy through KPI mappings. For instance, you might be planning to invest in stocks to build your savings and earn some extra income. But interpreting and understanding the trends and patterns of the market can be daunting. So, the use of graphical representations to show raw data allows viewers to comprehend and analyze deep insights into the data.
In this blog we will cover the following sections:
Visualizing data using Power BI
Since the human brain processes images 60,000 folds more than the text, visual elements such as graphs, charts, maps, etc, pave the way to identify relationships and analyze patterns with the help of interactive visualization tools. There are swamping options, Microsoft Power BI, Tableau, and Qlik Sense, just to mention a few of the data visualization tools to save data analysts or executives from going through the boring spreadsheets. Phew!
Talking about Microsoft’s Power BI is a business analytics service that helps in analyzing and visualizing data from various sources to craft data stories and share them with the end-users. Power BI is a combination of the following services and applications which work for hand in glove to create and share interactive business insights-
- Power BI Desktop– a Windows desktop application
2) Power BI Service – an online SaaS (Software as a Service) service.
- Power BI Mobile – for Android, iOS, and Windows devices
Now as you have got a picture of what Power BI is, let me answer a question that most of you might be wondering. What differentiates Power BI from other BI tools? The below points will illustrate the key benefits –
- Real-time dashboard updates
- Secure, live connection to multiple sources, even on-premises, and cloud
- Integrated with well-known Microsoft products
- Fast deployment, hybrid configuration
Getting acquainted with Power BI Desktop
Before diving into the concepts of Power BI Desktop, let us revisit the real-time problem of understanding the stock market which we had discussed in the beginning. So, to solve this problem, firstly, we need to download this 32/64-bit desktop application. And here is a catch- it is freely downloadable!
You can use the link: https://powerbi.microsoft.com/en-us/getting-started-with-power-bi/
Or download it from Microsoft Store from your browser.
Now, let’s get started by connecting to a data source and building our Power BI reports.
With Power BI Desktop, we can connect to data from many different sources, which are divided into the following categories:
And to connect to the required data, select the Get Data option from the Home ribbon. A pop-up displays data types as shown in the following image-
After we have connected to our data, we can use it for visualization by shaping and transforming (if required) our data and building dashboards and reports. But before we get into this process, let us have a look at the three Power BI Desktop views which help us to get the most out of our data
- Report view:
This is the default view where we create our reports by arranging the visualizations including different graphs, charts, and a lot more, according to our requirements over multiple pages in a single report.
- Data view:
When we are modeling our data, sometimes without creating a visual on the canvas, we would like to see the loaded table or column. This view helps us to view data in a grid format; piece by piece to analyze it closely.
- Model view:
This view helps us to see the relationships between different tables and also the columns they comprise of.
Perform Data Cleaning
Since we deal with a large volume of data from multiple sources, there are chances that our data might be incorrect or have discrepancies in a variety of ways. So before getting into the action of visualizing this data it is very essential to prepare this raw data by cleaning, transforming, and modeling this data before further use.
You might have noticed when we were loading our data into Power BI, we came across two options- one was Load and the other was Transform Data. If we click on the latter option, another window launches. This is known as the Power Query Editor.
One more thing to be noted is we can also transform data by clicking on the Transform Data icon from the Home tab of Power BI Desktop.
Power Query Editor includes a plethora of features that assist us in cleaning and preparing our data for analysis. Now let me break down the Power Query user interface for you.
1) In the middle of the Power Query Editor screen, we can see the data of the selected query.
2) On the left side, all the available queries(tables) are listed in the Queries pane.
3) On the right side, we can see all the steps which we took to shape our data are listed in the Query Settings pane, along with the query’s properties.
4) And on the top, we can see the ribbon contains several actions that can be used to select view, and shape our data.
Data Modeling in Power BI
As explained above in this blog, we know that data modeling is done in the Model View in Power BI Desktop. Here we can see all the tables, their columns, and the relationships between them, which depicts how the different sources are connected.
Now let’s refer to the above figure, you can see thatNIFTY Table 1 has anIndex column which is related to theNIFTY Table 2, which also has anIndexcolumn. We see it’s aMany-to-One(*:1) relationship, and the icon in the middle of the line depicts the cross-filter direction is set toBoth.
When you hover the cursor over the relationship, it highlights the column used to create it. And if you want to make any changes to the relationship, you can double-click on it and the Edit Relationship dialog box will appear.
Understanding DAX Functions and creating measures
Microsoft extensively uses DAX, Data Analysis Expressions, to create required information using the existing tables and columns. This programming language is used to calculate and return one or more values.
Now let us create a measure from our data. Click on this icon to write a new measure.
This measure includes the following syntax elements:
- The measure name is Total Turnover.
- The equals sign operator (=) shows the beginning of the formula.
- The DAX function SUM adds up all the numbers in the NIFTY Table1[Turnover] column.
- Parentheses contain one or more arguments for the expression. The argument passes a value to a function.
- The referenced table NIFTY Table1.
The referenced column [Turnover] is in the table. This is the argument where the SUM functions know to aggregate the SUM.
The below lists will help you know more about various DAX functions.
Different ways to visualize data in Power BI
Power BI comes with several visuals, including pie charts, maps, and bar charts. It also includes complicated models such as funnels, gauge charts, a cascade, and a variety of other elements. The default visualization icons are shown in the figure below.
We may utilize custom visuals in Power BI to help us see data in a way that fits our requirements which cannot be fulfilled with the in-built visuals. These custom visuals can be easily imported or created as per our use.
Let’s check out the below table which can help us incorporate some basic visualizations into our report which we will publish-
To make more data-driven decisions, it has become fundamental to analyze the data and create readable visualizations of quality. Despite there are many reporting tools in the market, Microsoft Power BI Desktop is great for visual data exploration as it enables simple and quick visualization of data.Top Trending Tech Articles:
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