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Today's advanced guide to capitalizing on analytics: the start-to-finish resource for both analytics students and practitioners
Advanced Analytics Methodologies is today's definitive guide to analytics implementation for MBA and university-level business students and sophisticated practitioners. Its expanded, cutting-edge coverage helps readers systematically "jump the gap" between their organization's current analytical capabilities and where they need to be.
Step by step, Michele Chambers and Thomas Dinsmore help readers customize a complete roadmap for implementing analytics that supports unique corporate strategies, aligns with specific corporate cultures, and serves unique customer and stakeholder communities. Drawing on work with dozens of leading enterprises, Michele Chambers and Thomas Dinsmore provide advanced applications and examples not available elsewhere, describe high-value applications from many industries, and help you systematically identify and deliver on your company's best opportunities. They show how to:
This advanced text will serve the needs of students and faculty studying cutting-edge analytics techniques, as well as experienced analytics leaders and professionals including Chief Analytics Officers; Chief Data Officers; Chief Scientists; Chief Marketing Officers; Chief Risk Officers; Chief Strategy Officers; VPs of Analytics or Big Data; data scientists; business strategists; and many line-of-business executives.
Download the sample pages (includes Chapter 9 and Index)
Chapter 1: Principles of Modern Analytics 1
Chapter 2: Business 3.0 Is Here 15
Chapter 3: Why You Need a Unique Analytics Roadmap 19
Chapter 4: Analytics Can Supercharge Your Business Strategy 25
Chapter 5: Building Your Analytics Roadmap 61
Chapter 6: Analytic Applications 87
Chapter 7: Analytic Use Cases 103
Chapter 8: Predictive Analytics Methodology 119
Chapter 9: Predictive Analytics Techniques 147
Chapter 10: End User Analytics 193
Chapter 11: Analytic Platforms 223
Chapter 12: Attracting and Retaining Analytics Talent 257
Chapter 13: Organizing Analytics Teams 283
Chapter 14: What Are You Waiting For? Go Get Started! 293
Appendix A: Unsupervised Learning: Unsupervised Neural Networks 297