Microsoft Power BI was designed as a business analytics service that allows you to bridge the gap between data and decision-making. Microsoft offers this suite of several helpful products and services that add value to your business operations by working together.
It can also connect to most of the popular databases and cloud-based data sources. This post is intended to provide an overview of Power BI and a quick introduction to getting started with it.
Table of Contents
- Introduction to Power BI
- Understanding the Features and Applications of Power BI
- Understanding the Working of Power BI
- Limitations of Power BI
Introduction to Power BI
Power BI is a business analysis tool from Microsoft that can be used as a cloud service or as a standalone on-premise installation. It lets users connect to various data sources and ask questions about the data through queries.
It also lets users transform data into reports and dashboards to aid decision-making. Being an offering from Microsoft, Power BI offers tight integration to all the Microsoft ecosystem components like SQL Server, Microsoft Azure databases, etc. It can integrate with Microsoft active directory and hence fits well into most organizations’ default security and authentication protocols. Its strengths are not limited to Microsoft components.
- Access to a free Power BI desktop account and application.
- Basic understanding of business analysis.
Understanding the Features and Applications of Power BI
Power BI is not the name of a single application, but the umbrella term for a collection of applications that are suited for different purposes. They are listed below.
- Power BI Desktop
- Power BI Report Server
- Power BI Service
- Power BI Mobile
- Power BI Embedded
Power BI Desktop is the most basic application. As the name suggests, it can be installed in standalone mode on a desktop. It is offered free of cost and can be connected to various data sources. It enables users to analyze data and derive insights from the data. It can connect to on-premise as well as cloud-based data sources. Power BI Desktop is not available via the web and is an independent stand-alone analysis tool. Beyond the ad-hoc analysis tool use case, it also acts as the development environment for creating reports and dashboards that can be deployed later.
Power BI Report Server is a web application that can be deployed on-premise to let the users in an organization view the reports and dashboards. The reports and dashboards that are designed through the Power BI Desktop can be deployed in the report server. It supports a level of interactivity for the reports and dashboards.
Power BI Service is the cloud-based business intelligence tool that is available based on a subscription from Microsoft. It lets the users take advantage of Power BI Analytics features without having to spend time with deployment or maintenance. It can connect the most common on-premise and cloud-based data sources. In the back end, it works based on Microsoft Azure compute clusters. This enables it to handle large data volumes and streaming data. It is offered based on different subscription plans like premium and pro depending upon the feature sets.
Power BI Mobile is Microsoft’s attempt to bring Power BI to mobile devices. In the back end, it also makes use of the Power BI Service. All the actual data processing happens in cloud servers and the mobile application serves as the front end for displaying interactive dashboards and reports.
Power BI Embedded helps users to enable Power BI features in their custom web applications. It enables developers to control the user experience while letting their customers have access to the power of analytics in a familiar environment.
Beyond data modeling and analysis, it also boasts machine learning capabilities enabling even people without data science skillsets to build machine learning models based on text and images.
It offers numerous benefits like streamlined publication and distribution, the ability to work with real-time information while working on dashboards, and the ability to customize the security features in a tool that is very easy to set up and requires no additional training to get your customized dashboards up and running.
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Understanding the Working of Power BI
A Power BI workflow can generally be set up through the following four broad steps:
- Connect to the data source.
- Model the data source into the required form.
- Create reports and dashboards.
- Publish them through Power BI Service or Report Server hosted on-premise.
The first step towards getting started is to head to the Power BI Desktop download page and install it. Follow the sequence below to work with a sample dataset to create a report.
- Step 1: Once installed, you will be greeted with the below view. Report view is the default welcome screen. Click Get Data to start connecting the data.
- Step 2: Select the ‘Web’ option and paste the link ‘https://www.bankrate.com/retirement/best-and-worst-states-for-retirement/’ as the input. This link has data regarding different cities categorized based on parameters like affordability, crime rate, culture, etc.
- Step 3: This will prompt you with a ‘Load’ dialogue. You can choose to transform the data if you wish to.
- Step 4: You can play around with the various options to do operations like removing columns, transforming columns, etc.
- Step 5: To create a report, head to the report view and drag visualization to the canvas. For example, you can drag the state field from the right side to the canvas. It is intelligent enough to recognize it as a geographical field and create geographical visualization for you.
- Step 6: When you are done adding the visualizations, Select File and Click ‘Save’ to save the report.
- Step 7: You can then click on the ‘Publish’ button to publish the report to the connected service.
That concludes the short sequence in getting started with Power BI. Now that you are familiar with how to work around it, the next question is whether it suits your use case. To decide on that, you may want to hear about the limitations as well.
Limitations of Power BI
- The processing is intelligent enough to make use of the underlying database’s processing capabilities in most cases. But in some cases, it can not do it and needs to import data. In such cases, the data volume for processing is limited to 1 GB.
- The above limitation also makes its presence felt in the number of rows as well. It cannot process more than 10 million rows of data as the output of the analysis queries.
- It handles the most simple queries elegantly but gets into trouble when there are queries that involve multiple tables joins.
- The Data Connector support in the case of open-source NoSQL databases and cloud-based sources other than the Microsoft Azure environment is not great. For example, it does not support cloud-based data sources like Hubspot. It also does not work well with NoSQL databases like MongoDB.
You can solve the data connector limitations by using a cloud-based ETL tool like Hevo.
This article talks about Microsoft Power BI in great detail. It helps you understand the various features, applications, and limitations of leveraging Power BI as a part of your data analysis pipeline to help improve efficiency.
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