Over the past decade, data science has come out of the back office to become a force of change across the entire organization. At the forefront of this change is the open data science movement that advocates the use of open source tools in a powerful, connected ecosystem. This report explores how open data science can help your organization break free from the shackles of proprietary tools, embrace a more open and collaborative work style, and unleash new intelligent applications quickly. Authors Michele Chambers and Christine Doig explain how open source tools have helped bring about many facets of the data science evolution, including collaboration, self-service, and deployment. But you’ll discover that open data science is about more than tools; it’s about a new way of working as an organization. Learn how data science—particularly open data science—has become part of everyday business Understand how open data science engages people from other disciplines, not just statisticians Examine tools and practices that enable data science to be open across technical, operational, and organizational aspects Learn benefits of open data science, including rich resources, agility, transparency, and collective intelligence Explore case studies that demonstrate different ways to implement open data science Discover how open data science can help you break down department barriers and make bold market moves Michele Chambers, Chief Marketing Officer and VP Products at Continuum Analytics, is an entrepreneurial executive with over 25 years of industry experience. Prior to Continuum Analytics, Michele held executive leadership roles at several database and analytic companies, including Netezza, IBM, Revolution Analytics, MemSQL, and RapidMiner. Christine Doig is a senior data scientist at Continuum Analytics, where she's worked on several projects, including MEMEX, a DARPA-funded open data science project to help stop human trafficking. She has 5+ years of experience in analytics, operations research, and machine learning in a variety of industries.

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.

Create a complete roadmap for capitalizing on analytics to grow topline revenue and build shareholder value in your unique organization! Modern Analytics Methodologies goes far beyond the classic Analytics Maturity Model to help you overcome the gaps between your current analytics capabilities and where you need to go. Pioneering analytics experts Michele Chambers and Thomas Dinsmore help you implement analytics that supports your strategy, aligns with your culture, and serves your customers and stakeholders. Drawing on work with dozens of leading enterprises, Michele Chambers and Thomas Dinsmore describe high-value applications from many industries, and help you systematically identify and deliver on your company's best opportunities. Writing for both professionals and students, they show how to: Leverage the convergence of macro trends ranging from "flattening" and "green" to Big Data and machine learning 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 Modern Analytics Methodologies will be an indispensable resource for any executive or professional concerned with analytics, 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 line-of-business executives.