Business analytics : a data-driven decision-making approach for business. Volume II, Predictive analytics / Amar Sahay, PhD.

Chapter 1. Business analytics at a glance -- Chapter 2. Business analytics and business intelligence -- Chapter 3. Analytics, business analytics, data analytics, and how they fit into the broad umbrella of business intelligence -- Chapter 4. Descriptive analytics--overview, applications, and a case -- Chapter 5. Descriptive versus predictive analytics -- Chapter 6. Key predictive analytics models (predicting future business outcomes using analytic models) -- Chapter 7. Regression analysis and modeling -- Chapter 8. Time series analysis and forecasting -- Chapter 9. Data mining: tools and applications in predictive analytics -- Chapter 10. Wrap-up, overview, notes on implementation, and current state of business analytics.

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This business analytics (BA) text discusses the models based on fact-based data to measure past business performance to guide an organization in visualizing and predicting future business performance and outcomes. It provides a comprehensive overview of analytics in general with an emphasis on predictive analytics. Given the booming interest in analytics and data science, this book is timely and informative. It brings many terms, tools, and methods of analytics together. The first three chapters provide an introduction to BA, importance of analytics, types of BA--descriptive, predictive, and prescriptive--along with the tools and models. Business intelligence (BI) and a case on descriptive analytics are discussed. Additionally, the book 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 concluding chapter discusses the current state, job outlook, and certifications in analytics.

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Description based on PDF viewed 11/14/2019.