The impact of Business Intelligence on Business Decision-Making for Performance Improvement: a data-driven approach with advanced technologies

This thesis explores the role of Business Intelligence (BI) in enhancing data-driven decision-making within modern organizations. Chapter 1 gives an overview of Business Intelligence definitions, which highlight its capability to act as a bridge between data collection and decision making. It examines its historical evolution through these recent years, underlining the necessity to be more conscious about company’s strategical data and to have a direct and on-time view over company’s performance. It discusses the main differences compared to other data subjects. Moreover, it analyses the life cycle of BI projects, as an iterative process focused on adapting to business requirements and strategic planning, highlighting BI’s benefits and limitations. Chapter 2 and chapter 3 investigate how BI tools (Microsoft Power BI in particular) and methodologies - such as data warehousing, analytics and visualization - enable businesses to transform raw data into actionable insights. It analyses all the process starting from data extraction, through data cleaning and manipulation, until the visualization of dashboards and useful information extracted from data. By analysing a real case study in chapter 4, the research highlights the strategic value of BI in improving cost management, decision-making and creating a competitive advantage. The study also addresses challenges related to data quality, integration and user adoption, offering recommendations for successful BI implementation. Ultimately, the thesis underscores BI's critical role in supporting agile, informed and forward-looking business strategies in a rapidly evolving digital landscape, explaining and presenting successful performance and cost management improvements leaded by BI tools.