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Sinopsis
The Definitive Guide to Enterprise-Level Analytics Strategy, Technology, Implementation, and Management
Organizations are capturing exponentially larger amounts of data than ever, and now they have to figure out what to do with it. Using analytics, you can harness this data, discover hidden patterns, and use this knowledge to act meaningfully for competitive advantage. Suddenly, you can go beyond understanding “how, when, and where” events have occurred, to understand why – and use this knowledge to reshape the future. Now, analytics pioneer Tom Davenport and the world-renowned experts at the International Institute for Analytics (IIA) have brought together the latest techniques, best practices, and research on analytics in a single primer for maximizing the value of enterprise data. Enterprise Analytics is today’s definitive guide to analytics strategy, planning, organization, implementation, and usage. It covers everything from building better analytics organizations to gathering data; implementing predictive analytics to linking analysis with organizational performance. The authors offer specific insights for optimizing supply chains, online services, marketing, fraud detection, and many other business functions. They support their powerful techniques with many real-world examples, including chapter-length case studies from healthcare, retail, and financial services. Enterprise Analytics will be an invaluable resource for every business and technical professional who wants to make better data-driven decisions: operations, supply chain, and product managers; product, financial, and marketing analysts; CIOs and other IT leaders; data, web, and data warehouse specialists, and many others."Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
THOMAS H. DAVENPORT, (Cambridge, MA) co-founder and Director of Research of the International Institute for Analytics, a world renowned thought leader and executive advisor on analytics. His book, Analytics at Work: Smarter Decisions, Better Results, was named a must-read for 2010 by CIO Insight. Davenport holds a Ph.D. from Harvard University, taught at Harvard Business School, and led research centers at McKinsey and CSC. He is President's Distinguished Professor of Information Technology and Management at Babson College; senior advisor, Deloitte Analytics, Deloitte Touche Tohmatsu; and member, Board of Sponsors, MIT Center for Information Systems.
De la contraportada
The Definitive Guide to Enterprise-Level Analytics Strategy, Technology, Implementation, and Management
• From the International Institute for Analytics, the world’s premier analytics research organization
• Proven best practices for choosing projects and technology, building analytics organizations, and measuring ROI
• Brand-new case studies from finance, healthcare, technology, retail, manufacturing, and beyond
As businesses recognize the immense potential of analytics, they are increasingly treating it as an enterprise resource and an enterprise priority. Now, the world’s leading researchers on large-scale analytics have brought together today’s best practices for planning, implementing, managing, and succeeding with analytics on an enterprise level.
Drawing on their pioneering work at the International Institute for Analytics, the authors illuminate the entire analytics lifecycle, addressing technology, applications, operations, governance, strategy, and more. They offer actionable solutions for leveraging proprietary data, gaining a new 360-degree view of the customer, measuring engagement in actionable ways, optimizing “next best offers,” applying analytics at production scale, using cloud resources, and linking analytics directly to business performance. Then, in a full section on the crucial human side of analytics, they address everything from building and governing analytics organizations to integrating analytics throughout global businesses.
Whether you’re an analyst, manager, strategist, executive, or technology vendor, this book will help you implement large-scale analytics faster, avoid crucial missteps, and capture far more value.
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Enterprise analytics. Optimize performance, process, and decisions through big data.
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Enterprise analytics. Optimize performance, process, and decisions through big data.
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Upper Saddle River, FT Press, 2013
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