Fundamentals of business intelligence

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This book offers a systematic introduction to transforming process-oriented data into valuable insights for decision-making. The authors present step-by-step models and analytical tools designed to structure high-quality data for complex analyses. Focusing on process mining and data mining techniques, the text explores the integration of these methods for process-oriented data. Beginning with an overview of the business intelligence (BI) process and its tasks, the book progresses through various topics: modeling approaches in BI applications, data provisioning—including big data considerations, data description and visualization, and reporting techniques. It also delves into data mining for cross-sectional data and analyzes temporal data, followed by methods for examining process data and multiple BI perspectives. The final chapter summarizes and discusses the key points. Throughout, the book recommends and describes mostly open-source tools, with a detailed appendix on tools and code solutions available on an accompanying website. Concepts are illustrated with examples and exercises, making it suitable for graduate students in computer science. The dedicated website enhances its value as a textbook for introductory courses in business intelligence, while practitioners and developers will find the clear explanations and examples beneficial.