個案資料

Business analytics is an emerging area in modern business decision-making, gaining interest and popularity. This book discusses the models based on fact-based data to measure past business performance in order to guide organizations in visualizing and predicting future business performance and outcomes. Bringing terms, tools, and methods of analytics together, a comprehensive overview of analytics is given with an emphasis on predictive analytics. The book provides an introduction to and types of business analytics, the importance of analytics, and business intelligence. It also discusses the most widely used predictive models, including regression analysis, forecasting, data mining, and an introduction to recent applications of predictive analytics - machine learning, neural networks, and artificial intelligence. The current state, job outlook, and certifications in analytics are also examined. Chapter 3 builds on chapter 2, discussing how analytics, business analytics, and data analytics all fit into business intelligence and going further into the comparison between business analytics and business intelligence. Business intelligence is a technology-driven process for processing and analyzing data to make sense from huge quantities of data that businesses collect and obtain from various sources. It is both visualization and analytics. Various functions and applications of business intelligence are described, including but not limited to reporting, online analytical processing, and business process management. Business intelligence can combine external and internal data in order to create an "intelligence" that cannot be derived by any one set of data. Business intelligence along with business analytics can empower organizations and give them a better understanding of the existing markets and customer behavior.

• Technology and analytics
• Predictive analytics
• Data processing
• Management performance
• Business analysis
• Decision making