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Descriptive Analytics-Overview, Applications, and a Case
內容大綱
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 provides a more in-depth look at descriptive analytics. Descriptive analytics tools are used to understand the occurrence of certain business phenomena or outcomes and explaining these outcomes through graphical, quantitative, and numerical analyses. A case is given to demonstrate the tools and applications of visual techniques used in descriptive analytics. Descriptive analytics is critical in studying the current state of a business and in learning what has happened in the past using company data. Knowledge derived from descriptive analytics lays a foundation for further analysis and leads to predictive analytics.