Power BI Tutorial - A Complete Guide for Beginners

Prior to delving into Power BI, it is advantageous to understand business intelligence. Business intelligence encompasses an assemblage of methodologies and utilities employed for scanning the unprocessed data. It pertains to the strategies and techniques adopted by enterprises to conduct a comprehensive analysis of pertinent business information. Business intelligence operates through ETL processes, which involve extracting, transforming, and loading data into a database, encompassing activities like data mining, online analytical processing, and business reporting. Numerous organizations leverage business intelligence to enhance their overall efficiency and operational efficacy.

Microsoft Power BI is a tool that converts data from various data sources into interactive BI reports and dashboards. With Power BI, you can quickly connect your data, wrap it, visualize it as needed, and share it securely across sites.

Watch the video below to learn Power BI:

For organizational success, making informed decisions based on available data is crucial. Microsoft Power BI was created to fetch relevant data and present it in an easily understandable format. Once created by Ron George, it was first called Crescent. Later, with the help of Thierry D’Hers and Amir Netz of Microsoft’s SQL Server Reporting Services team, it became Power BI. Released as Power BI for Office 365 in September 2013, it became publicly available on July 24, 2015. This tool swiftly transforms raw data into meaningful, useful information.

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The following are the main Power BI components :

• Power Query: The Power Query is an important component that is used for searching, accessing, and transforming public and internal data sources.
• Power Pivot: Data modeling for in-memory analytics in Power BI is taken care of by Power Pivot.
• Power View: You can visualize, analyze, and display data in Power BI with the help of Power View.
• Power Map: The Power Map creates interactive geographical data visualizations.
• Power BI Service: By using Power BI Service, you can share data views and workbooks and refresh from on-premises and cloud-based data sources.
• Power BI Q&A: The Power BI Q&A allows you to ask questions and get prompt answers using a natural language query.
• Data Management Gateway: The Data Management Gateway provides regular data refreshers, views data feeds, and exposes tables.
• Data Catalog: By using Data Catalog, the user can discover along with reusing queries using the Data Catalog. Also, this kind of functionality can be facilitated by using Metadata.

Power BI Architecture typically consists of a data foundation layer, a data analytics engine, and a data visualization dashboard.

Data Foundation

Different file formats from different cloud data sources can be harmonized and brought into a unified data model by using Power BI. Power BI can integrate with various cloud sources, such as Azure Dataverse, and different data formats such as flat files and .csv.

Data Analytics

Power BI offers a wide range of analytics functionalities, encompassing descriptive and diagnostic capabilities. Leveraging DAX-based logic and analytical frameworks, Power BI enables the execution of diverse analytical calculations and experiments on the underlying data infrastructure. Moreover, Power BI seamlessly integrates with cloud-based machine learning platforms like Azure ML, enhancing its analytical potential.

Data Visualization

Power BI offers various visualizations, simple and complicated, for creating state-of-the-art insights-driven dashboards. Power BI has easy-to-use and intuitive visualization capabilities, making visualization from unified data models straightforward to implement and execute.

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Data Sources

Power BI incorporates a diverse range of data sources that play a pivotal role in its functionality. These data sources enable Power BI to establish connections and retrieve data from both local files within the system and online cloud-based repositories. Several illustrative examples of these data sources include:

• Excel
• Power BI Datasets
• Power BI Dataflows
• Dataverse
• SQL Server
• Analysis Services
• Text or CSV
• Web
• OData Feed
• Blank Query
• Power BI Template Apps
• MySQL Database
• Google Analytics
• Facebook
• GitHub

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Power BI provides interactive visualization of data with self-service business intelligence capabilities. With Power BI, end users can create their own interactive business intelligence reports and dashboards without depending on IT personnel or database administrators. Most organizations use Power BI as their business analytics solution.

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Difference Between Power BI and Tableau

Many individuals often confuse Power BI and Tableau because both are utilized for data analysis and visualization. However, there are distinct differences between these two tools which are as follows:

Next in this Power BI Tutorial, we will go through some of the essential Power BI tools:

1-  Power BI Service

Also known as Power BI Online, Power BI Service is a web-based platform allowing you to share reports on the Power BI Desktop. The Power BI Service facilitates ease of collaboration with users and creating dashboards and reports. It is a Software-as-a-Service (SaaS) tool that hosts Power BI models, dashboards, and reports. Sharing reports, administrative operations, and collaboration all happen with the help of the Power BI Service. However, it is only available with the pro license, for which a user must pay US$10 monthly.

Power BI Service lets you ask questions about your data. There are three versions of Power BI, the Free Version, the Pro Version, and the Premium Version.

All in all, Power BI Service is one of the building blocks of Power BI; Power BI Service lets you create, share, and consume business insights.

2- Power BI Desktop

The Power BI Desktop is a free data analytics and visualization tool that allows users to create data models, dashboards, and reports. Connecting with multiple available data sources becomes easier with the help of the Power BI Desktop. Most users working on business intelligence projects depend on Power BI Desktop for creating and sharing reports. The main uses of Power BI Desktop are:

• Connecting to multiple data sources
• Data visualization
• Creating reports
• Data transformation
• Sharing reports

The three views available with Power BI Desktop are Report View, Data View, and Model View.

3-  Power BI Report Server

Power BI Report Server is an on-premise platform that allows you to display and manage reports and KPIs. It hosts paginated reports, dashboards, power applications, and KPIs. You can modify the existing reports, created by the development team, and use filters to get a customized experience. You can access reports on web browsers or mobile devices. The reports can also be accessed via email.

4-  Power BI Gateway

Installed by the BI admin, Power BI Gateway bridges Power BI and on-premises data sources such as Excel, DirectQuery, PowerApps, Azure Analysis Services, etc. The data extracted through secure channels, with the help of Power BI Gateway, is used for analysis and reporting. Power BI Gateway provides ease of access to data as it directly connects the client platform to the on-premises source.

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5-  Power BI Mobile

Power BI Mobile is a mobile application that can run on iOS, Android, and Windows. Power BI Mobile allows you to view reports and dashboards anywhere and anytime.

6- Power BI Apps

Power BI Apps are mobile applications available for Windows, iOS, and Android devices. Using Microsoft Intune, you can share reports and dashboards with other users, which they can access on their smartphones over the internet.

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Power BI Dashboards

The Power BI Dashboard is basically a page consisting of visualizations to represent a story or business insight. It is limited to only one page and can be viewed and shared on mobile devices as well. The visualizations that are seen on the dashboard are obtained from reports that are gathered from datasets.

 Advantages of the Power BI Dashboard

The interactive visualizations available on the Power BI Dashboard are considered one of the best ways to monitor business. All the metrics can be viewed at a glance. The Power BI Dashboard is also known as Canvas, as it consists of a single page. This is going to make it easier for you to have a clear view of the metrics in spite of multiple reports from different datasets.

The following is a sample screenshot of the Power BI Dashboard:

Power BI allows you to create reports with multiple perspectives from one dataset, later stored in the Power BI Report Server. These reports are known as Power BI reports. You can create and edit the reports on the Power BI desktop and publish them on the web portal. Post-publication, the readers can view the reports in a web browser or the Power BI Mobile on a mobile device. The reports in Power BI can have one or more visual pages.

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Data Analysis Expressions (DAX) in Power BI is a formula expression language used to create calculated fields and apply them to datasets. DAX offers a collection of operators, functions, and constants that can be used to create formulated columns and rows for better understanding. DAX has different data types, such as numeric, decimals, currency, integers, binary objects, and strings.

Also, read about Power BI vs Excel.

How does it work?

To understand the workings of Power BI DAX, it is very important to understand the three key concepts in Power BI DAX- Syntax, Context, and Functions.

1. Syntax

The syntax is basically the Power BI formula, which consists of many components. To write effective DAX syntax, it is suggested that you break the formula into understandable language. Consider the simple syntax below:

Total Sales = SUM ( Sales [sales amount] )

In the above syntax,

Total Sales refers to the measure name

The beginning of the DAX formula is denoted by ‘=’

‘SUM’ is used to add up all the figures in the column

‘( )’ Parenthesis means the expression consists of more than one argument

2. Context

Context is considered an important Power BI DAX concept. It can be explained by enlisting its two types- Row Context and Filter Context.

Row Context is,, simply speaking, the current row and is used especially in the case of measures. Row context is applied to a formula where the function uses filters to identify a single row in a table.

In simpler terms, Filter Context means that there is one more filter applied in a calculation. It is a difficult context to understand as compared to the Row context. Usually, it is not possible that the Filter context is applied in place of the Row Context. But it is not possible for the Filter Context to be applied in addition to the Row Context.

3. Functions

Functions in Power BI refer to the predefined, ordered, and structured formulae to carry out calculations using arguments. Some of the common DAX functions are MIN, MAX, SUM, AVERAGE, MAXX, SUMX, and more.

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Calculated Columns and Measures

‘Calculated columns’ are nothing but the extension of a table using the DAX formulas to add new columns while creating data models on the Power BI Desktop. Also, the content to be added in the new columns is defined by a DAX expression.

‘Measures’ are a different way of defining calculations in DAX models. Basically, they are used when you are not operating on a row-by-row basis but are doing so on aggregated values that are defined by the current context.

In Power BI, you should first connect your data to the tool, transform the data that you have uploaded, model the data as needed, visualize the data, and share the generated results.

Connecting Your Data

You can either use Power BI or Power BI Desktop to connect a variety of data sources, such as MySQL Server, MySQL, Oracle, etc. You can connect your data to Power BI in two ways either upload your file to Power BI or import the file into Power BI.

Uploading your File to Power BI

Connect to the data in your workbook to create Power BI reports and dashboards for it.

Importing your File into Power BI

In order to view your file, you will have to fetch it in Power BI; you can interact with the file just as you would do in the case of Excel Online.

Transforming Your Data

Once your data is loaded, you can transform it as per your needs. You can do this by using the Transform menu. It has a set of operations, including reverse rows, count rows, rename, replace values and errors, pivot and unpivot columns, etc.

Modeling Your Data

For data modeling, add the data sources in Power BI’s new report option. Power BI lets you add functions, calculations, relationships, measures, etc., to your data for better visualization and analytics; this is done so that the data can be used to derive better business insights. This functionality of Power BI is referred to as Data Modeling. By using Power BI Data Modeling, you can even write a query to your files so that you can accomplish different tasks in a short span of time.

Data Visualization

In Power BI, you can create reports, dashboards, etc. based on the modeled data and depending on your organization’s requirements. Report creation can be done in many ways; you have to select a field of your choice from your CSV or data file, and then choose the tool that you want to give to your data so as to generate the desired report. You can use a variety of tools and even add a custom visual gallery.

The following are some samples of data visualization:

Sharing the Generated Reports

To share a generated report, select the ‘Share’ option that appears in the top navigation. Select the ‘share’ option, complete the form, and share it with your team.

On selecting the ‘share’ option, complete the form, and share it with your team.

You can share the generated reports from Favorites, Recent, and My Workspace.

There are many companies that use Power BI for efficient decision-making. Computer software companies are the largest segment of companies that use Power BI. Some companies that use Power BI are:

• Microsoft
• Oracle
• IBM
• Tableau Software
• SAP
• Dell
• Wipro

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The following are the advantages of using Power BI:

• Has a short learning curve as compared to other BI tools such as Tableau
• Simple and easy-to-use interface with drag-and-drop features for data visualization
• Introduces new functionalities and data analysis functions almost every month
• Crowning features allow you to create customized dashboards and meet exact organizational demands
• The power natural language interface lets you run database queries through voice commands
• Allows the author to connect with live data sources and provides the information to the stakeholders in real-time

The following are the disadvantages of using Power BI:

• Reports and dashboards can only be shared with users with the same email domain
• You cannot merge data from live connections with on-premise datasets. Instead, you have to connect all data sources to the Power BI Server and publish your dashboard on the website
• Power BI only accepts datasets with a maximum size of 250 MB for its in-memory database. If a dataset is larger in size, then you have to run direct queries on the database, which makes the process much slower
• Few data sources and parameters as compared to Tableau

In this Power BI step-by-step tutorial, you learned that Power BI is a business intelligence tool through which you can make creative reports and dashboards for better decision-making. You also learned about business intelligence, its importance, how Power BI came into existence and importance, the working of Power BI, companies using Power BI, etc. You will learn about the building blocks of Power BI in the next session.