What is Power BI?
The use of Power BI in data science and data analysis has become increasingly popular for the past few years. But what is Power BI? Is it an effective tool? What features make it stand out from the rest? Should you use it for data analysis? This blog will help you get answers to all these questions and more.
Introduction
Power BI is a Microsoft-developed business intelligence tool that can turn raw data into actionable insights through analysis and visualization. It allows users to connect to various data sources, clean and prepare data, explore, analyze, and visualize data, and create interactive dashboards and reports to help organizations make informed decisions.
This technology was recognized as a leader in the analytical field by Gartner in February 2019, which named Microsoft as the leader in the “2019 Gartner Magic Quadrant for Analytics and Business Intelligence Platform” due to the capabilities of the Power BI platform.
Power BI Components
Power Query
It is a data transformation and mash-up engine that enables users to discover, connect, combine, and refine data sources to serve analysis purposes. You can download it as an add-in for Excel or use it as part of Power BI Desktop.
Power Pivot
This data modeling technique allows the creation of data models, the establishment of relationships, and the creation of calculations using the DAX language.
Power View
This feature allows the creation of interactive charts, graphs, maps, and other visuals to bring data to life. You can use the benefits of Power View in Excel, SharePoint, SQL Server, and Power BI.
Power Map
It is a 3D data visualization tool that enables the mapping of data and visual plotting of more than a million rows of data using Bing Maps in 3D format.
Power BI Desktop
This development tool combines Power Query, Power Pivot, and Power View into one solution, making it easier to develop BI and data analysis experiences.
Power Q&A
It is a BI feature that allows users to explore data using natural language queries, providing a fast way to get answers from data. An example query could be “What were the profits last year?”
You can learn more about the components of Power BI, its tools, features, etc. by taking a Power BI course online. The best thing about taking an online course is that you can access it from anywhere and learn at your own pace.
Power BI Features
Power BI Q&A (Natural Language Queries)
It is a natural language processing (NLP) feature, allowing users to ask questions about their data in plain language and receive answers in the form of visualizations. It is easy to use and helps reduce the time and effort required to find insights and make data-driven decisions. Power BI Q&A also supports various question types, such as comparison, trend analysis, and prediction to make the tool more versatile.
Power BI DAX (Data Analysis Expressions)
This is a formula language that helps create calculated columns and measures in Power BI. DAX provides a range of functions and operators that allow you to manipulate and aggregate data, perform calculations, and create complex expressions.
Power BI DAX helps you to create calculations that were previously impossible to solve in a traditional pivot table, such as calculating moving averages, running totals, and year-to-date values.
Power BI APIs for Data Integration and Automation
A range of APIs integrated with Power BI, this feature allows you to integrate and automate various aspects of the platform. You can use the APIs to automate the data refresh process, retrieve data from other sources, and perform custom actions within Power BI. With these APIs, you can automate repetitive tasks and streamline your workflow, making it easier to manage and analyze your data.
Benefits of Power BI
Ease of Use
With an advanced UX-UI design, Power BI provides a user-friendly interface that makes it easy for data scientists to connect to data sources, clean and transform data, and create visualizations. It offers an aesthetically pleasing experience with an easy-to-use drag-and-drop functionality and the ability to copy formatting across similar visualizations.
Integration with Other Tools
You can easily integrate Power BI with other Microsoft tools such as Excel, Azure, and SQL Server.
Advanced Visualization
It provides advanced visualization capabilities, allowing data scientists to create interactive visualizations to communicate insights effectively.
Automated Data Transformation
It has the option to automate data transformations, which helps free up time for data scientists to focus on more complex analysis tasks.
Real-Time Data Streaming
Power BI supports real-time data streaming, therefore, allowing data scientists to work with live data and make quick decisions based on the latest information.
Streamline Big Data Preparation with Azure
By combining Power BI with Azure, quick analysis and sharing of large amounts of data are possible. Therefore, it helps increase collaboration among business analysts, data engineers, and data scientists.
Mobile Access
Power BI has a mobile app that allows data scientists to access and interact with their reports and dashboards on the go.
Advanced Calculation Capabilities
With advanced calculation capabilities through its DAX formula language, Power BI eases the work in the data science field by performing complex data manipulations and time-series analysis.
Power BI Visualizations
With the advancement of technologies and innovations, Power BI has become a powerful business intelligence tool that provides a wide range of visualization options for data science and data analysis. Some of the most commonly used visualizations in Power BI for data analysis include bar charts, line charts, pie charts, scatter plots, and maps. In addition, you can also use some advanced visualization options such as tree maps, heat maps, and sunburst charts, to help uncover deeper insights from data.
The intuitive drag-and-drop interface in Power BI helps create visualizations more efficiently, making it easy to explore patterns and relationships in data. When the users select the type of visualization they wish to create, they can select the data they wish to use, and then customize the visualization to meet their specific needs.
For example – Users can filter data to show any specific time periods, highlight specific data points, or change the color and style of the visualization.
The Power BI Developer tools allow users to create custom visualizations using HTML, CSS, and JavaScript. It provides them with complete control over the look and feel of the visualization. With customization, it becomes possible to create visualizations tailored to the specific needs of the data science project, providing greater insights and better decision-making capabilities.
Power BI Dashboards
The dashboard provides a centralized view of all the visualizations, reports, and data sets used in a data science project and makes the tool easy to navigate. Dashboards are highly customizable and you can design them to meet the specific needs of your project.
To create a dashboard in Power BI, you can start with a blank canvas and add visualizations, reports, and other data sources as required. For instance, you can add bar charts, line charts, and other types of visualizations to show trends and patterns in data. You can also add performance reports or summary reports to provide more context and detail on any specific aspects of the data.
It is easy to share Power BI Dashboards with team members and stakeholders, making it easy to collaborate on data science projects. Users can grant access to specific individuals, groups, or the entire organization, and can also set permissions for editing and viewing the dashboard. Therefore, it promotes collaborative work and makes it easy for the team members to view the dashboard and contribute to the data science project, regardless of their location or device.
Power BI and Machine Learning
If someone asks ‘what is power bi used for’, it will be impossible to contain the answer within one or two uses. With new advancements, Power BI is constantly upgrading itself to offer more advanced features. Power BI provides integration with machine learning algorithms to allow you to create predictive models and perform analysis within the platform.
It supports the use of R and Python, the two most popular programming languages for machine learning, and integrates with Azure Machine Learning. In addition, it provides a range of algorithms for performing tasks such as classification, regression, clustering, and dimensionality reduction to offer a complete solution for data analysis.
Conclusion
With the rapid growth of big data and the increasing importance of data-driven decision-making, Power BI will be one of the top choices for data scientists. The advanced tools have made it possible for professionals to quickly get the answers they need, even from the largest and most complex data sets. With its powerful data compression algorithms, easy-to-use interface, add-on machine learning, and advanced features, Power BI has revolutionized the field of data science.
