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. This chapter offers an overview of business analytics and business intelligence and outlines the similarities and differences between the two. Business analytics, types of analytics, and the analytics process are all explained. Different tools used in each type of analytics are discussed as well as their relationship and interconnection. These tools overlap in applications and a combination of these tools can be used in many situations. In comparing business analytics and business intelligence, business analytics, data, analytics, and advanced analytics all fall under the wide scope of business intelligence. Business intelligence tools include the business analytics tools but also include data mining, online analytical processing, and business performance management among other things.

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