How to get started with Power BI?: Step by Step guide

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. 

What is 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.

Prerequisites

• Access to a free Power BI desktop account and application. 
• Basic understanding of business analysis. 

Power BI Versions and Features

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. It 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.

10 Reasons to Use Power BI

How do you know if Power BI is the right choice for your business? Here are the top 10 reasons to help you make this decision:

• Affordable: It provides a 1GB data limit for free that allows you to enjoy most of the powerful capabilities such as building reports & dashboards, manipulating data, scheduling data refreshes, sharing dashboards, etc. You can also opt for a Power BI Pro license that starts at $9.99 per user per month.
• Handy Visualisations: With the drag n drop functionality, you can simply pick and place data fields from your sources to your dashboards and reports.
• Easy Connections: With 70+ in-built connectors, you can easily build your reports from data sources such as Azure (Azure Data Warehouse), DropBox, Google Analytics, OneDrive, and SalesForce, in addition to Excel spreadsheets, CSV files, and data located on-premises, such as SQL Database.
• Secure: You can rest assured about data governance & protection protocols with Azure Active Directory (AAD) built-in for user authentication, allowing you to leverage Single Sign-On (SSO), along with your regular Power BI login credentials to access your data.
• MS Excel Familiarity: Users who are well versed with advanced Excel features like Data Analysis Expressions (DAX) formula language, Power Pivot & Power Query tool can quickly get started with Power BI.
• Real-Time Sync: You can start working with fresh data as your Dashboards get updated in real-time.
• Data Modeling: There are built-in predictive forecasting models that automatically identify seasonality and the upcoming reporting period (week, month, year) and project the forecasting results with graphical visualization.
• Natural Language Queries: With Power BI integration with Microsoft’s digital assistant Cortana, you can type in a question like “What is the total revenue for this year?” and Power BI will provide you an answer in the form you like.
• Best-In-Class Performance: It can efficiently deal with tables in excess of 100 million records without slowing down as compared to Excel. It is optimized to compress databases and make sure that they load fully into memory for optimal performance.
• Market Leader: Dominating the BI Market, Power BI has come out on top for the 13th consecutive year in the Gartner 2020 Magic Quadrant for Analytics and Business Intelligence Platforms.

Most Popular Data Sources for Power BI

Data sources supported by Power BI can be classified into the following categories:

• Files: Power BI Desktop supports the most commonly used data format files for recording data such as Excel Workbook, Text/CSV, XML, JSON, Folder, PDF, Parquet & SharePoint folder. Power BI service also allows you to import the Power BI Desktop file(.pbix) into your Power BI site.
• Databases: The Desktop product provides extensive database connections such as PostgreSQL, MySQL, Amazon Redshift, Snowflake, BigQuery, Oracle, SQL Server, etc.
• Azure: The Service product allows you to connect directly to databases present on the cloud such as Azure SQL Database, Spark on Azure HDInsight & Azure Synapse Analytics. With the Desktop version, you can connect to more platforms such as Azure SQL Database, Azure Synapse Analytics SQL, Azure Analysis Services database, Azure Blob Storage, Azure Data Explorer (Kusto), Azure Databricks, etc.
• Other: This includes miscellaneous sources such as Web, SharePoint list, Microsoft Exchange, Hadoop File (HDFS), Spark, Hive LLAP, R script, Python script, ODBC, Google Sheets (Beta), Microsoft Teams Personal Analytics (Beta), etc.

Getting Started with Power BI Desktop

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. 

You can explore more about power BI integration : Firebase Power BI Integration.

Conclusion

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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