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Key Predictive Analytics Models (Predicting Future Business Outcomes Using Analytic Models)
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. Chapter 6 explains key models used in predictive modeling. These models are the core of predictive analytics and are used to predict future business outcomes. Explanations and application areas of each tool are given. The tools described include various types of regression models, forecasting models, ANOVA, data mining, machine learning, artificial intelligence, neural networks, and deep learning.