The main goal of this project is to evaluate how data analytics tools and techniques are revolutionizing managerial decision-making in modern enterprises. Specifically, the project aims to explore three key applications: the role of business intelligence in enhancing high-level strategic decisions; the use of predictive analytics in e-commerce to improve customer retention and lifetime value; and the impact of HR analytics in performance evaluation and talent management. The study aims to showcase how a data-driven culture can lead to more informed, objective, and impactful decisions across different departments. By the end of the project, students will present case-based insights into how analytics directly influences outcomes and provides organizations with a competitive edge.
To execute this project, students will begin by reviewing literature on business intelligence platforms (e.g., Tableau, Power BI), predictive modeling techniques (e.g., regression, clustering), and HR analytics tools (e.g., dashboards, KPIs). They will identify relevant case studies or conduct primary research through surveys or interviews with managers, HR professionals, or e-commerce analysts.
Further tasks include data collection and cleaning, application of data visualization or machine learning models (based on the selected focus area), and interpretation of patterns that can inform better decisions. Students may also simulate predictive models using sample datasets to evaluate factors affecting customer churn or employee performance. The project culminates with a comprehensive report and presentation that includes analytical findings, business implications, and strategic recommendations.
