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Prescriptive Analytics

- The Final Frontier for Evidence-Based Management and Optimal Decision Making

Om Prescriptive Analytics

This book is written for both professionals who are interested in developing a holistic understanding about business analytics and especially about prescriptive analytics and college students, both at graduate and undergraduate levels, who are in need of a nicely balance book between theory and practice to explain prescriptive analytics as the top layer in business analytics continuum. • End-to-end, all-inclusive, holistic approach to prescriptive analytics—not only covering optimization and simulation, but also including multi-criteria decision-making methods along with inference- and heuristic-based decisioning techniques. • Enhanced with numerous conceptual illustrations, example problems and solutions, and motivational case and success stories. • Chapter 1 -- overview of business analytics, its longitudinal perspective and a simple taxonomy, and where prescriptive analytics fits into this big picture. • Chapter 2 -- introduces the topic of optimization and describes different types of optimization methods using simple yet practical examples and application cases. • Chapter 3 -- explains simulation, including Monte-Carlo simulation, discrete and continuous simulation, as a powerful tool to analyse complex systems to make better decisions. • Chapter 4 -- introduces multi-criteria decision making along with a simple taxonomy, and provides descriptions and examples of a variety of popular techniques used for multi-criteria problems commonly found in practice. • Chapter 5 -- about expert systems and case-based reasoning. • Chapter 6 -- introduces the latest techniques in analytics, namely Big Data, Deep Learning, and Cognitive Computing, as the leading edge for the next generation of automated decisioning and prescriptive analytics. Business analytics has been gaining popularity faster than any management trends we have seen in the recent history. As an attempt to unify the understanding of "what business analytics is,” the business community along with educational community have developed a simple taxonomy where they defined analytics using three progressive phases/echelons: descriptive/diagnostic analytics predictive analytics prescriptive analytics. This book is about prescriptive analytics, the highest echelon in the analytics continuum, and is the one closest to "making accurate and timely decisions.”

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  • Språk:
  • Engelska
  • ISBN:
  • 9780134387055
  • Format:
  • Häftad
  • Sidor:
  • 352
  • Utgiven:
  • 15. november 2019
  • Mått:
  • 141x229x12 mm.
  • Vikt:
  • 476 g.
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Leveranstid: Okänt - saknas för närvarande
Förlängd ångerrätt till 31. januari 2025
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Beskrivning av Prescriptive Analytics

This book is written for both professionals who are interested in developing a holistic understanding about business analytics and especially about prescriptive analytics and college students, both at graduate and undergraduate levels, who are in need of a nicely balance book between theory and practice to explain prescriptive analytics as the top layer in business analytics continuum.
• End-to-end, all-inclusive, holistic approach to prescriptive analytics—not only covering optimization and simulation, but also including multi-criteria decision-making methods along with inference- and heuristic-based decisioning techniques.
• Enhanced with numerous conceptual illustrations, example problems and solutions, and motivational case and success stories.
• Chapter 1 -- overview of business analytics, its longitudinal perspective and a simple taxonomy, and where prescriptive analytics fits into this big picture.
• Chapter 2 -- introduces the topic of optimization and describes different types of optimization methods using simple yet practical examples and application cases.
• Chapter 3 -- explains simulation, including Monte-Carlo simulation, discrete and continuous simulation, as a powerful tool to analyse complex systems to make better decisions.
• Chapter 4 -- introduces multi-criteria decision making along with a simple taxonomy, and provides descriptions and examples of a variety of popular techniques used for multi-criteria problems commonly found in practice.
• Chapter 5 -- about expert systems and case-based reasoning.
• Chapter 6 -- introduces the latest techniques in analytics, namely Big Data, Deep Learning, and Cognitive Computing, as the leading edge for the next generation of automated decisioning and prescriptive analytics. Business analytics has been gaining popularity faster than any management trends we have seen in the recent history. As an attempt to unify the understanding of "what business analytics is,” the business community along with educational community have developed a simple taxonomy where they defined analytics using three progressive phases/echelons: descriptive/diagnostic analytics predictive analytics prescriptive analytics. This book is about prescriptive analytics, the highest echelon in the analytics continuum, and is the one closest to "making accurate and timely decisions.”

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