Role of Power BI in data-driven decision-making in Modern Businesses

Business Intelligence uses various methods to extract useful information from existing data and provides that information to the right person at the right time in an easy-to-understand form. Microsoft Power BI serves as a transformative tool with powerful data analytics and visualization capabilities in Business Intelligence.

Data refers to information collected, stored, and analyzed to make decisions or draw conclusions. It can come in various forms, such as numbers, text, images, or any other format that can be processed and used for analysis. Data should be used to override intuition and gut-based decisions, as “data no longer is scarce or expensive, that rationale ceases to exist”.

Types of data generated by businesses

Access to high-quality data and data governance is essential for a data-driven organization. A data warehouse is a common location where data may have already been brought in, from which it can be extracted for analysis (Lu, Cairns, & Smith, 2021).

In the 21st century, with new technologies, data generated by businesses has expanded significantly. IT firms, IoT companies, social media advertisers, payment aggregators, and e-commerce aggregators generate structured and unstructured data.

Structured data refers to data that is organized in a pre-defined manner, typically in tables or databases. This type of data has a clear and consistent structure, making it easy to store, search, and analyze. Unstructured data refers to data that does not have a predefined data model or is not organized in a pre-defined manner. This data type is becoming increasingly prevalent, as it includes text, images, videos, and audio files. Unstructured data is typically more complex and less easily analyzed (Frisk & Bannister, 2017).

The need to visualize data

Visualizing data involves creating graphical representations of data, such as charts, graphs, and dashboards, to effectively communicate information and insights. Providing user-friendly tools and visualizations that cater to different user needs is essential for effective data visualization. It is an important aspect of business analytics, as it allows for the effective analysis and understanding of the data collected from various sources (Hiriyannaiah, G.M., & K.G., 2020). Thus, making it crucial for interpreting complex data sets, and making it easier for individuals and businesses to comprehend, analyze, and act upon data.

Modern data visualization tools, combined with the rise of big data analytics, have further enhanced the ability to explore and understand complex data through interactive, visual representations (Agrawal, 2014).

How does Power BI simplify data visualization?

Power BI and traditional spreadsheet tools like Excel both offer capabilities for creating charts and dashboards, but Power BI provides several advantages, especially for more advanced data analysis and visualization. Many analysts and business promoters are interested in exploring the source data itself and connecting different types of data to find optimal dimensions for analysis, rather than being limited to fixed dashboards (Frisk & Bannister, 2017). Power BI offers the flexibility to choose the data and its dimensions for specific analysis.

Power BI’s Power Query feature allows users to clean, transform, and load data from multiple sources seamlessly. While tools like Excel can connect to several data sources, they often require more manual setup with limited functionality.

Power BI supports real-time data streaming, enabling users to work with live data and monitor dashboards with up-to-the-minute information. Whereas, data in spreadsheets is static or requires manual refreshing, making real-time data analysis less feasible. Also, data transformation capabilities in Excel are present but are more manual and less robust compared to Power BI.

Power BI is also built to handle large volumes of data efficiently, leveraging cloud-based architecture to perform complex calculations and visualizations without slowing down. Power BI supports advanced data modeling, allowing the creation of complex relationships between data tables without performance issues.

Power BI components

Power BI offers the tools and flexibility required to meet a wide range of business intelligence needs. It consists of several components that work together to provide a full-fledged data analytics and visualization experience.

• Power BI Desktop: It is a free application installed on a local computer. It is the primary tool for connecting to data and creating data models, visualizations, and reports.
• Power BI Service Online: It is a cloud-based platform to publish, share, and collaborate on Power BI reports and dashboards. It’s accessible via a web browser.
• Power Query: It is a data connection technology to discover, connect, combine, and refine data across a wide variety of sources.
• Power Pivot: It is an in-memory data modeling component that helps to create complex data models, establish relationships, and perform calculations.
• Data Analysis Expressions (DAX): It is a formula language used in Power BI, Power Pivot, and SSAS Tabular models for creating custom calculations and aggregations.

Getting Started with Power BI Desktop

Installing Power BI Desktop is a straightforward process. Here’s a step-by-step guide to help you get started:

• Visit the official website of Power BI or download it directly from the Microsoft Store.
• If you’re using the Microsoft Store, it will automatically download and install the application. Otherwise, locate the .msi file in your downloads folder and double-click it to start the installation.
• Follow the on-screen instructions in the installation wizard.
• Once the installation is complete, click “Finish” to exit the installer.
• Power BI Desktop will be installed on your computer, and you can find it in the Start menu or as a desktop shortcut.

Launch the Power BI desktop and get around the interface

The Power BI Desktop interface is designed to be user-friendly. Launch the application on your desktop and choose to start with a “Blank Report”.

The Power BI Desktop interface is designed to provide users with a comprehensive set of tools for data import, transformation, modeling, and visualization. The interface is intuitive for users familiar with other Microsoft Office products.

References

• Agrawal, D. (2014). Analytics based decision making. Journal of Indian Business Research, 332-340. doi:https://doi.org/10.1108/JIBR-09-2014-0062
• Frisk, J. E., & Bannister, F. (2017). Improving the use of analytics and big data by changing the decision-making culture: A design approach. Management Decision, 00-00. doi:https://doi.org/10.1108/MD-07-2016-0460
• Hiriyannaiah, S., G.M., S., & K.G., S. (2020). Predictive Analytical Model for Microblogging Data Using Asset Bubble Modelling. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 108-118. doi:https://doi.org/10.4018/IJCINI.2020040107
• Lu, J., Cairns, L., & Smith, L. (2021). Data science in the business environment: customer analytics case studies in SMEs. Journal of Modelling in Management, 689-713. Retrieved from https://www.emerald.com/insight/1746-5664.htm