Abstract:

Power BI is a powerful business intelligence and data visualization tool that helps transform raw data into meaningful insights for research, business operations, and decision-making. In this seminar, I will introduce the fundamental components of Power BI, including Power Query for importing and transforming data, data modeling for organizing information, and Data Analysis Expressions for creating calculated measures. I will discuss principles of effective dashboard design, selecting appropriate visualizations, and developing key performance indicators to communicate meaningful patterns and trends.

Participants will see how to move from raw data to an interactive dashboard, including preparing data, creating visualizations, applying filters, and exploring results. Drawing on examples from applied data analytics, I will highlight how Power BI can support exploratory analysis, performance monitoring, and data-driven decision-making. By the end of the seminar, participants will have a foundational understanding of the Power BI workflow and how to get started building interactive reports.

Bio:

Mary Akinde is a Ph.D. candidate in Consumer Economics at the University of Georgia (UGA), where her research focuses on digital engagement, digital access, and psychological well-being among older adults. She holds a M.S. in Management and Analytics in Business from the National Research University Higher School of Economics in Saint Petersburg, Russia, and a B.S. in Economics (First Class Honors) from the Federal University of Agriculture, Abeokuta, Nigeria. She also has graduate-level training in Statistics at UGA.

Mary currently serves as a Data Analyst at the UGA Georgia Center for Continuing Education & Hotel, where she develops interactive Power BI dashboards, analytical reporting solutions, and performance metrics to support operational and strategic decision-making. Previously, she worked in analyst roles at UGA’s Franklin College Office of Academic Innovation and Union Bank of Nigeria.

Her expertise spans business intelligence, statistical analysis, modeling, data visualization, predictive analytics, and process automation and optimization. She is passionate about transforming complex data into actionable insights, automating analytical workflows, and making data-driven decision-making more accessible across academic and business environments