Paper Title
Data-Driven Decision-Making Analysis for Business Selection: A Power BI Approach

Abstract
In the dynamic realm of small enterprises, challenges often hinder success, ranging from inadequate market research to the absence of data-driven decision-making, particularly in location selection. This research advocates for implementation of Microsoft Power BI as a transformative solution, empowering small businesses to make informed decisions, particularly in the crucial domain of location suitability analysis. The study showcases Power BI's capacity to consolidate diverse data sources and offer user-friendly visualizations, bridging the gap in data-driven decision-making. The project focuses on practical examples, demonstrating Power BI's ability to transform complex datasets into intuitive visual representations. Emphasizing its user-friendly nature, the research provides a practical guide for small business owners, outlining the steps for implementing Power BI in location suitability analysis. Real-world case studies underscore the tangible benefits, showcasing successful business expansions, optimized operational costs, and improved customer targeting. In conclusion, this project positions Microsoft Power BI as a pivotal tool for small businesses, promoting a data-centric approach to decision-making for sustained success in the evolving business landscape. Keywords - Business Failure, Location Suitability Analysis, Data Driven Decision Making, Microsoft Power BI, Market Research.