Advanced Analytics Methodologies
Driving Business Value with Analytics
Published on 6. November 2014
Book
Hardback
336 pages
978-0-13-349860-8 (ISBN)
Description
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:
Go beyond the Analytics Maturity Model: power your unique business strategy with an equally focused analytics strategy
Link key business objectives with core characteristics of your organization, value chain, and stakeholders
Take advantage of game changing opportunities before competitors do
Effectively integrate the managerial and operational aspects of analytics
Measure performance with dashboards, scorecards, visualization, simulation, and more
Prioritize and score prospective analytics projects
Identify "Quick Wins" you can implement while you're planning for the long-term
Build an effective Analytic Program Office to make your roadmap persistent
Update and revise your roadmap for new needs and technologies
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.
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:
Go beyond the Analytics Maturity Model: power your unique business strategy with an equally focused analytics strategy
Link key business objectives with core characteristics of your organization, value chain, and stakeholders
Take advantage of game changing opportunities before competitors do
Effectively integrate the managerial and operational aspects of analytics
Measure performance with dashboards, scorecards, visualization, simulation, and more
Prioritize and score prospective analytics projects
Identify "Quick Wins" you can implement while you're planning for the long-term
Build an effective Analytic Program Office to make your roadmap persistent
Update and revise your roadmap for new needs and technologies
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.
More details
Persons
Michele Chambers is the Vice President of Marketing for MemSQL. Prior to this, she served as Chief Strategy Officer and Vice President of Product Management & Marketing for Revolution Analytics, General Manager and Vice President for IBM Big Data Analytics, and General Manager and Vice President for Netezza Analytics. In these roles, Michele has worked with hundreds of customers to help them understand how to use analytics and technology to achieve high-impact business value.
Thomas W. Dinsmore is the Director of Product Management for Revolution Analytics. Previously, he served as an Analytics Solution Architect for IBM Big Data, SAS Consulting, and PricewaterhouseCoopers. Thomas has helped more than 500 enterprises around the world use analytics more effectively. He uniquely combines hands-on skill in predictive analytics with business, organization, and technology experience.
Thomas W. Dinsmore is the Director of Product Management for Revolution Analytics. Previously, he served as an Analytics Solution Architect for IBM Big Data, SAS Consulting, and PricewaterhouseCoopers. Thomas has helped more than 500 enterprises around the world use analytics more effectively. He uniquely combines hands-on skill in predictive analytics with business, organization, and technology experience.
Content
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
Index 313
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
Index 313