Lesson 1 of 3By Avijeet Biswal
Last updated on Dec 7, 202030003Power BI is a technology-driven business intelligence tool provided by Microsoft for analyzing and visualizing raw data to present actionable information. It combines business analytics, data visualization, and best practices that help an organization to make data-driven decisions. In February 2019, Gartner confirmed Microsoft as Leader in the "2019 Gartner Magic Quadrant for Analytics and Business Intelligence Platform" as a result of the capabilities of the Power BI platform.
In this article, you will learn the following:
Now that we have looked at the topics we will be covering, let us go ahead and look at why Power BI becomes important.
Power BI is a business analytics service provided by Microsoft that lets you visualize your data and share insights. It converts data from different sources to build interactive dashboards and Business Intelligence reports.
As you see above, we have some sales data in an excel sheet. Using this data, Power BI helps you build different charts and graphs to visualize the data.
Now that you have learned what is Power BI, let us now understand why Power BI is required.
Following are the reasons why Power BI is so popular and needed in the BI domain:
Power BI can access vast volumes of data from multiple sources. It allows you to view, analyze, and visualize vast quantities of data that cannot be opened in Excel. Some of the important data sources available for Power BI are Excel, CSV, XML, JSON, pdf, etc. Power BI uses powerful compression algorithms to import and cache the data within the.PBIX file.
Power BI makes things visually appealing. It has an easy drag and drops functionality, with features that allow you to copy all formatting across similar visualizations.
Power BI helps to gather, analyze, publish, and share Excel business data. Anyone familiar with Office 365 can easily connect Excel queries, data models, and reports to Power BI Dashboards.
Using Power BI with Azure allows you to analyze and share massive volumes of data. An azure data lake can reduce the time it takes to get insights and increase collaboration between business analysts, data engineers, and data scientists.
Power BI allows you to gain insights from data and turn those insights into actions to make data-driven business decisions.
Power BI will enable you to perform real-time stream analytics. It helps you fetch data from multiple sensors and social media sources to get access to real-time analytics, so you are always ready to make business decisions.
Now, in this what is Power BI article, you will learn about the architecture of Power BI.
Power BI architecture is a service built on top of Azure. There are multiple data sources that Power BI can connect to. Power BI Desktop allows you to create reports and data visualizations on the dataset. Power BI gateway is connected to on-premise data sources to get continuous data for reporting and analytics. Power BI services refer to the cloud services that are used to publish Power BI reports and data visualizations. Using Power BI mobile apps, you can stay connected to their data from anywhere. Power BI apps are available for Windows, iOS, and Android platforms.
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Power BI service is the Software as a Service (SaaS) part of Power BI. It is also known as Power BI Online. To access Power BI Service, you need to log in to Power BI service.
Here is how the home page of Power BI Service looks like once you log in:
It allows you to connect to data, create reports and dashboards, and ask questions about your data.
Now, as you have understood what is Power BI, its architecture, and services, let us now understand about Dashboards in Power BI.
Power BI Dashboard is a single page visualization to tell a story. The visualizations on a dashboard are generated from reports, and each report is based on one dataset. A single page dashboard is known as a Canvas. Below is a Finance Dashboard published on Power BI Service.
The visualizations you see on the dashboard are called Tiles and are pinned to the dashboard by report designers.
Power BI allows you to create different reports on Power BI Desktop. These reports can be published on the Power BI dashboard using the Power BI service. A Power BI report created on Power BI Desktop can be published on to Power BI Service by clicking on the Publish button.
Let us now jump into learning the various components of Power BI.
Now, let's dive into understanding the Power BI features.
Following are some of the features of Power BI -
Now, to better understand what is Power BI, and how does it helps, let us look at a case study on how Meijer, which is one of the United States' largest supermarket chains, used Power BI to solve its business problems.
Meijer had significantly become dependent on its IT organization to extract insights from the data that is used to generate. It was time-consuming and inefficient to wait for IT to build every report. Meijer was unable to perform ad hoc and real-time analysis efficiently. So, Meijer connected Power BI to an on-premises SQL Server Analysis Services cube. This allowed them to refresh 20 billion rows of data in near real-time. With Power BI, teams can now pull in the data faster and perform real-time analysis to derive insights from data.
A bakery department inside Meijer used Power BI to compare its sales with regional performance. They analyzed where Meijer was behind the regional trends, focused on the problem, and created a solution. With Power BI, they can drill down into hourly sales and send out a sales flash to 800 Meijer business leaders. Power BI enabled them to standardize data sources and empower store directors and team leaders, to develop and track their data to ensure that they can improve.
With that, let us now jump into Power BI Desktop and do some practical hands-on demo using a Finance Sample Dataset. We will create a report to visualize different charts and graphs to analyze the sales made by various countries, products, and segments.
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In the Home Menu, click on the Get Data tab and choose Excel as your file source.
Select the data file from the system and click on Load. It will load the dataset onto the Power BI Desktop.
Give a title to the dashboard by creating a text box and naming it as Finance Dashboard. You can add a background color, select a specific font, and resize it as per your choice. From the Visualizations area, select a "card" and drag the sales column from Fields on to Values. This will show the total sales that were made. Similarly, you can select another "card" and drag the Units Sold column to show the total number of units that were sold.
Now, you see which product made what number of sales, you can create a simple Table from the Visualizations and drag Product and Sales columns on to the Values.
To check the total amount of sales made in each month and find out which month had the highest and lowest sales, you can create a simple clustered column chart and drag the date column on the Axis and the Sales on to the values. You can change the color of the bars by going to the Format option and selecting Data Colors.
As you can see from the above chart, October month had the highest amount of sales and March had the least.
Then create a pie chart to analyze the sales made by each segment and find out which segment made the highest and lowest amount of sales. Click on the pie chart option, select Segment on to the Legend, and Sales on to the Values.
As you can see from above, the Government segment made the highest sales with 52.5M comprising of 44.22% from the total, while Channel Partners made the lowest.
You can also create a map that will depict the sales made in each country. Select Map from Visualizations and add the Country column in the location and Sales column under Size.
Using a Donut chart, you can see the Profit made in each Segment.
So, the Government segment made the highest profit, with 65.04%. Finally, visualize which Product gave us the highest revenue. We'll create a Treemap and add the Product column under Group and Sales under Values.
So, the product Paseo gave us the highest revenue.
Below is how our two-page report looks like:
After reading this article, you would have understood the need for Power BI in Business Intelligence, what is Power BI, and the various features of Power BI. You also learned about Power BI Service, how to create a Dashboard in Power BI, and how the architecture looks like. Finally, you explored the different features of Power BI Desktop by creating different visualizations to analyze finance sample data.
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Avijeet is a Senior Research Analyst at Simplilearn. Passionate about Data Analytics, Machine Learning, and Deep Learning, Avijeet is also interested in politics, cricket, and football.
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