Repository Collections

In today’s fast-changing business environment, decisions can no longer rely solely on intuition or past experience. Organizations generate vast amounts of data through customer interactions, financial transactions, digital platforms, and operational systems, making data analytics an essential tool for decision-making. This chapter explores how businesses can transform raw data into meaningful insights by applying statistical methods and analytical models. It outlines the foundations of descriptive, diagnostic, predictive, and prescriptive analytics, and demonstrates their application through real-world cases from retail, banking, healthcare, manufacturing, and e-commerce. By blending statistical rigor with practical examples, the chapter shows how analytics helps businesses forecast trends, reduce risks, and improve efficiency. It also highlights common challenges such as data quality, ethical issues, and skill shortages, while pointing to future opportunities in artificial intelligence, real-time processing, and sustainability-focused analytics. The discussion emphasizes that when used responsibly, data analytics is not just a support system but a driver of competitive advantage and innovation.
Keywords: Business, Environment, Data Analytics, Decision-Making, Predictive Models, Business Intelligence and Artificial Intelligence