Krystallis, IliasAbussaud, Laian2025-06-152025https://hdl.handle.net/20.500.14154/75521The construction industry faces persistent challenges in financial management, including cost overruns, tight profit margins, and unpredictable project variables. This dissertation investigates the transformative role of data analytics in addressing these challenges and enhancing profitability in construction projects. By comparing projects that implement data-driven financial strategies with those using traditional methods, the study employs a quantitative, quasi-experimental design to assess key financial performance indicators such as cost variance, profitability, and return on investment. Drawing from secondary datasets and real-world case studies, the research demonstrates how historical and real-time data, predictive modeling, and integrated analytics tools contribute to improved cost estimation, resource allocation, and risk mitigation. Findings indicate that comprehensive utilization of data analytics significantly enhances financial outcomes, providing a compelling case for its broader adoption in the industry. The study not only bridges a critical research gap but also offers practical recommendations for construction firms, project managers, and policymakers seeking to harness analytics for sustainable financial success.21enData AnalyticsFinancial ManagementConstruction ProjectsThesis