Power BI for Data Science

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What is Power BI? Microsoft’s business analytics product, Power BI, delivers interactive data visualization BI capabilities that allow users to see and share data and insights throughout their organization. Power BI provides insight data by using data interactively and exploring it by visualizations.

Why Power BI?

Customer Feedback

Power Bi is used for data analytics and visualization. Power BI has been a pioneer in applying AI through capabilities such as natural language, which enables users to get answers by asking questions in plain English, or Quick Insights, which automatically finds patterns in data.

Today, we’re taking a major step forward in bringing AI to business intelligence and announcing several new AI features in Power BI that are available in preview.

  • Users can now get capabilities such as image recognition and text analytics directly in Power BI.
  • Key driver analysis helps users understand what influences key business metrics.
  • Users can create machine learning models directly in Power BI using automated machine learning.
  • Users now have seamless integration of Azure Machine Learning within Power BI.

All these new AI capabilities—pioneered in Azure and now available in Power BI—require no code. This enables all Power BI users to discover hidden, actionable insights in their data and drive better business outcomes with easy-to-use AI.

  • Jayant Bose, M.Sc. Maths; PGDM IIMC:

Power BI provides cloud-based BI services, known as “Power BI Services”, along with a desktop based interface, called “Power BI Desktop”. It offers data warehouse capabilities including data preparation, data discovery and interactive dashboards.

Key components of the Power BI ecosystem:

Power BI Desktop

The Windows-desktop-based application for PCs and desktops, primarily for designing and publishing reports to the Service.

Power BI Service

The SaaS (software as a service) based online service (formerly known as Power BI for Office 365, now referred to as Power BI | Interactive Data Visualization BI Tools or simply Power BI).

Power BI Mobile Apps

The Power BI Mobile apps for Android and iOS devices, as well as for Windows phones and tablets.

Power BI Gateway

Gateways used to sync external data in and out of Power BI. In Enterprise mode, can also be used by Flows and PowerApps in Office 365.

Power BI Embedded

Power BI REST API can be used to build dashboards and reports into the custom applications that serves Power BI users, as well as non-Power BI users.

Power BI Report Server

An On-Premises Power BI Reporting solution for companies that won’t or can’t store data in the cloud-based Power BI Service.

Power BI Visuals Marketplace

A marketplace of custom visuals and R-powered visuals.

BiSmart: 6 reasons why you should do data analytics with Power BI

  • Data connection
  • Data visualization
  • Advanced analytics 
  • Data governance
  • Data exploration
  • UX & UI


Rise of Microsoft Power BI as a Data Analytics Powerhouse

Get started with Power BI Desktop

Python in Power BI

R in Power BI

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ML in a Power BI Dashboard

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Visualize Twitter Data with Power BI

Word cloud visualization in Power BI


Data Analysis Expressions (DAX) is a library of functions and operators that can be combined to build formulas and expressions in Power BI, Analysis Services, and Power Pivot in Excel data models.

Pros & Cons

  • The user interface of Power BI is intuitive, and it can easily be integrated with other Microsoft products. Power BI Desktop provides three views that you can select on the left side of the canvas – the report view, the data view, and the model view.
  • Power BI supports various data sources (Microsoft Excel, Text/CSV, Folders, MS SQL Server, Access DB, Oracle Database, IBM DB2, MySQL database, PostgreSQL database, etc.) but has limited access to other databases and servers compared to Tableau.
  • Power BI has an edge because of its ease of use since it is based on a user interface that has its roots in Microsoft Office 365, which most end-users are already familiar with.
  • Power BI supports Data Analysis Expression and M language for data manipulation and data modeling. It can also connect to the R/Python programming language using Microsoft revolution analytics, but it is available only for enterprise-level users. 
  • Power BI provides an easy to use drag and drop functionality. It provides features that make data visually appealing. Power BI offers a wide range of detailed and attractive visualizations to create reports and dashboards. 
  • Power BI enjoys the advantages of Microsoft business analytics that includes platforms such as Azure Machine learning, SQL Server based Analysis Services, data streaming in real-time, and many Azure databases offers. 
  • Microsoft Power BI is relatively younger in the market than Tableau and hence has a smaller community.
  • The Google Trends for Power BI and Tableau suggests, Tableau is more popular and widely searched for the internet. Even on YouTube, Tableau is more popular compared to Power BI in terms of search volume.
  • For 13 consecutive years, Gartner has recognized Microsoft as a Magic Quadrant Leader in analytics and business intelligence platforms. It has recognized Tableau as a leader in Business Intelligence after Microsoft.

Explore More

Get samples for Power BI

Tutorial: From Excel workbook to a report in the Power BI service to Microsoft Teams
Tutorial: From Excel workbook to stunning report in Power BI Desktop

View a dashboard

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Power BI Tip — How to custom sort categorical/text columns in a bar chart?

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Power BI A-Z: Hands-On Power BI Training For Data Science!

Getting Started with Data Analysis using Power BI

Power BI Downloads


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