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The text is designed for first-year business students with no prior knowledge of business or statistics. It introduces the cross-industry standard process for data mining, providing a systematic approach to business problem recognition and solution. The book offers a high-level overview of analytical methods used in business, including descriptive, diagnostic, predictive, and prescriptive analytics, and covers their applications in real-world business cases. The first half of the book focuses on using spreadsheets, a widely used tool in the industry, while the second half prepares students for the ever-evolving business environment by introducing R. From a statistical perspective, the book covers fundamental concepts such as descriptive statistics and probabilities. Students will learn to use descriptive statistics to identify outliers and apply conditional probabilities to make predictions. Each chapter is based on real-life business cases and is accessible to first-year students. Faculty members interested in adopting the book for their course will have access to a complete set of lecture slides, a test bank including quiz questions for each chapter, midterm and final exams, and an end-of-term project in the form of creating an interactive dashboard. The test bank and cases are updated annually to keep pace with the latest developments in the field.