Disruptive Analytics: Charting Your Strategy for Business Analytics 2.0 teaches corporate personnel and consultants what they need to know about seven key technology trends rocking the world of predictive analytics.
Each of these seven technology trends—the spread of open source analytic software, the inception of a new generation of analytic databases, the proliferation of the Hadoop ecosystem and cluster architectures, the refinement of new techniques of machine learning, the mass automation of predictive model lifecycles in model factories, the migration of data warehousing and analytics services to cloud computing platforms, and the improvements in business intelligence visualization appliances—is radically changing how businesses use data for competitive advantage. Taken together, these seven trends are a perfect storm disrupting every link in the business analytics supply chain: the vendors, the hires, and the accountabilities within organizations.
As with any wave of disruptive technologies, nimble organizations seize the opportunity to grow and profit while rigid organizations dither and decline.Disruptive Analytics provides corporate personnel and consultants a roadmap for aligning people, processes, and technology to capture the competitive benefits of these seven disruptive technologies. It shows corporate personnel and consultants how to select the analytics technologies that are optimal for a given enterprise, how
to maximize ROI with the best mix of open source and proprietary tools and software, how to hire the new breed of analysts with the requisite skill sets, and how to remove the structural and cultural barriers to assimilating disruptive technologies into an organization.
Through case studies of real-world products, vendors, and implementations, analytics authority Thomas W. Dinsmore describes from a practical management perspective the business impacts on enterprises of the seven disruptive technologies, considered both individually and together.
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About the Author |
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About the Technical Reviewer |
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Acknowledgments |
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Introduction |
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Chapter 2 A Short History of Analytics |
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Chapter 3 Open Source Analytics |
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Chapter 4 The Hadoop Ecosystem |
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Chapter 5 In-Memory Analytics |
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Chapter 6 Streaming Analytics |
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Chapter 7 Analytics in the Cloud |
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Chapter 8 Machine Learning |
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Chapter 9 Self-Service Analytics |
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Chapter 10 Handbook for Managers |
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Index |
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Thomas W. Dinsmore is Knowledge Expert in Customer Analytics at The Boston Consulting Group. He previously served as Director of Product Management for Revolution Analytics; Analytics Solution Architect for IBM Big Data Solutions; and Principal Consultant for SAS Professional Services. Dinsmore has more than twenty-five years of experience in predictive analytics. He led or contributed to analytic solutions for more than five hundred clients across vertical marketsincluding AT&T, Banco Santander, Citibank, Dell, J. C. Penney, Monsanto, Morgan Stanley, Office Depot, Sony, Staples, United Health Group, UBS, and Vodafoneand around the worldincluding the United States, Puerto Rico, Canada, Mexico, Venezuela, Brazil, Chile, the United Kingdom, Belgium, Spain, Italy, Turkey, Israel, Malaysia, and Singapore. Although his roots are in hands-on customer analytics, in the past fifteen years Dinsmore has expanded the scope of his experience to include analytic software applications and broader solutions including database integration and web applications. As a project lead, he has worked with DB2, Oracle, Netezza, SQL Server, and Teradata. Dinsmore is certified in SAS 9 and has working experience with the Hadoop ecosystem and the leading analytic tools in the market today, including SAS, R, SPSS, and Oracle Data Mining. Dinsmore is the author of Modern Analytics Methodologies (FT Press, 2014) and Advanced Analytics Methodologies (FT Press, 2014) and runs The Big Analytics Blog. He holds his MBA from the Wharton School, The University of Pennsylvania, and his bachelors from Boston University.