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Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data, CourseSmart eTextbook

By Thomas H. Davenport

Published by Pearson FT Press

Published Date: Sep 10, 2012

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The amount of data that business professionals are presented with has grown exponentially. The field of analytics gives professionals the ability to not only understand data, but see patterns in it. Rather than simply answering questions about what, how, when, where things have happened, analytics pushes further, to find out why things are happening, what will happen if these trends continue, and how information can be used to optimize outcomes. Analytics combines tools and methods to examine what already happened, to predict what will happen, and to explore what should happen. It allows professionals to tackle large amounts of data, harness it and transfer it into information that will lead to meaningful action. The first book published by Tom Davenport and the International Institute for Analytics -- drawn from the IIA's exclusive research and writings, Enterprise Analytics delivers the most current insights on the evolution of the field, but more importantly it offers proven strategies and guidelines for the most effective implementation of data analytics and predictive analytics. Replete with examples from across industries, the book will show readers how to implement analytics in their own organization. From the supply chain to online services, in healthcare, financial services, and marketing, readers will learn how to use analytics to bring the power of data to current and future decisions and actions of the firm.

Table of Contents

Foreword and Acknowledgments     xii
Jack Phillips
About the Authors    xiv
Introduction: The New World of Enterprise Analytics
Thomas H. Davenport

Part I:  Overview of Analytics and Their Value
Chapter 1  What Do We Talk About When We Talk About Analytics?     9
Thomas H. Davenport

Chapter 2  The Return on Investments in Analytics     19
Keri E. Pearlson

Part II:  Application of Analytics
Chapter 3  Leveraging Proprietary Data for Analytical Advantage     37
Thomas H. Davenport

Chapter 4  Analytics on Web Data: The Original Big Data     47
Bill Franks

Chapter 5  The Analytics of Online Engagement     71
Eric T. Peterson

Chapter 6  The Path to “Next Best Offers” for Retail Customers     83
Thomas H. Davenport, John Lucker, and Leandro DalleMule

Part III:  Technologies for Analytics
Chapter 7  Applying Analytics at Production Scale     97
James Taylor

Chapter 8  Predictive Analytics in the Cloud     111
James Taylor

Chapter 9  Analytical Technology and the Business User     123
Thomas H. Davenport

Chapter 10  Linking Decisions and Analytics for Organizational Performance     135
Thomas H. Davenport

Part IV:  The Human Side of Analytics
Chapter 11  Organizing Analysts     157
Robert F. Morison and Thomas H. Davenport

Chapter 12  Engaging Analytical Talent     179
Jeanne G. Harris and Elizabeth Craig

Chapter 13  Governance for Analytics     187
Stacy Blanchard and Robert F. Morison

Chapter 14  Building a Global Analytical Capability     203
Thomas H. Davenport

Part V:  Case Studies in the Use of Analytics
Chapter 15  Partners HealthCare System     215
Thomas H. Davenport

Chapter 16  Analytics in the HR Function at Sears Holding Corporation     233
Carl Schleyer

Chapter 17  Commercial Analytics Culture and Relationships at Merck     241
Thomas H. Davenport

Chapter 18  Descriptive Analytics for the Supply Chain at Bernard Chaus, Inc.     249
Katherine Busey and Callie Youssi

Index     255

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Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data, CourseSmart eTextbook
Format: Safari Book

$22.49 | ISBN-13: 978-0-13-303948-1