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Advanced Analytics Methodologies: Driving Business Value with Analytics Hardcover – 22 Sep 2014

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From the Back Cover



  • Shows how to create analytics roadmaps that maximize topline revenue and shareholder value
  • Demonstrates cutting-edge strategies, techniques, and cases, from identifying opportunities to choosing algorithms
  • Reflects the experience of two pioneering analytics/ Big Data experts with dozens of enterprise implementations
  • Essential for advanced students and practitioners using any platform or toolset

In this comprehensive, cutting-edge guide, two of the field’s most experienced implementers show you how to systematically optimize the business value of analytics.


Michele Chambers and Thomas W. Dinsmore show how to build a complete analytics roadmap you can successfully execute on: one that fully reflects your business strategies, culture, customers, resources, and competitive environment. They present important new applications and case studies, revealing how sophisticated organizations are increasing short- and long-term value across five key areas: strategic, managerial, operational, scientific, and customer-facing analytics.


Chambers and Dinsmore guide you in linking analytics strategy to specific tactics and techniques, thoroughly informing your choices of tools, algorithms, and platforms. They provide valuable new insights into the impact of Big Data on predictive analytics, and demystify important new technologies such as Apache Spark for Hadoop.


Drawing on their unsurpassed enterprise experience, they also address make-or-break management issues—including how to organize effective analytics teams, find outstanding data scientists, and retain them.


This is today’s definitive guide to analytics implementation for MBA and university-level business students and sophisticated practitioners. Its cutting-edge coverage helps you systematically “jump the gap” between your current analytical capabilities and where you need to be, so you can use analytics to efficiently grow revenue, profitability, and market share.


Michele Chambers and Thomas W. Dinsmore help you customize a complete roadmap for implementing analytics that supports your corporate strategies, aligns with your culture, and serves your customer and stakeholder communities.


Drawing on work with dozens of enterprises, they provide advanced examples and high-value use cases from multiple industries, and help you systematically identify and deliver on your best opportunities. They address both high-level strategies and specific techniques: everything from identifying game-changing applications to assessing the tradeoffs of each algorithmic approach.


This advanced text will serve the needs of students and faculty studying cutting-edge analytics techniques, as well as experienced analytics leaders and professionals, data scientists, business strategists, and line-of-business executives.

Execute on Today’s 9 Core Principles of Analytics Success

  • Build and continuously evolve analytics for high-value business impact
  • Focus on the last mile: deploy into production to gain repeatable, ongoing value
  • Leverage Kaizen to start small and build upon success
  • Accelerate learning and execution: do, learn, adapt, repeat
  • Differentiate your analytics to produce new results
  • Embed analytics throughout your key business processes
  • Establish a modern architecture that drives out cost
  • Maximize and groom analytics talent
  • Capitalize on consumerization, leveraging new choices to innovate

About the Author

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.


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