Leaders and Innovators How Data-Driven Organizations Are Winning with Analytics

by Nguyen, Tho H.; Taylor, James; Franks, Bill

• ISBN13: 9781119232575
• ISBN10: 1119232570
• Edition: 1st
• Format: Hardcover
• Copyright: 2016-09-06
• Publisher: Wiley

Summary

An integrated, strategic approach to higher-value analytics

Leaders and Innovators: How Data-Driven Organizations Are Winning with Analytics shows how businesses leverage enterprise analytics to gain strategic insights for profitability and growth. The key factor is integrated, end-to-end capabilities that encompass data management and analytics from a business and IT perspective; with analytics running inside a database where the data reside, everyday analytical processes become streamlined and more efficient. This book shows you what analytics is, what it can do, and how you can integrate old and new technologies to get more out of your data. Case studies and examples illustrate real-world scenarios in which an optimized analytics system revolutionized an organization's business. Using in-database and in-memory analytics along with Hadoop, you'll be equipped to improve performance while reducing processing time from days or weeks to hours or minutes. This more strategic approach uncovers the opportunities hidden in your data, and the detailed guidance to optimal data management allows you to break through even the biggest data challenges.

With data coming in from every angle in a constant stream, there has never been a greater need for proactive and agile strategies to overcome these struggles in a volatile and competitive economy. This book provides clear guidance and an integrated strategy for organizations seeking greater value from their data and becoming leaders and innovators in the industry.

• Streamline analytics processes and daily tasks
• Integrate traditional tools with new and modern technologies
• Evolve from tactical to strategic behavior
• Explore new analytics methods and applications

The depth and breadth of analytics capabilities, technologies, and potential makes it a bottomless well of insight. But too many organizations falter at implementation—too much, not enough, or the right amount in the wrong way all fail to deliver what an optimized and integrated system could. Leaders and Innovators: How Data-Driven Organizations Are Winning with Analytics shows you how to create the system your organization needs to dramatically improve performance, increase profitability, and drive innovation at all levels for the present and future.

Author Biography

THO H. NGUYEN works closely with customers across industries, research and development, and business partners to drive and deliver value-added business solutions in analytics, data warehousing, and data management. Over his eighteen-year career, he has extensive experience applying his technical and business skillsets to strategy development, product management, global marketing, and business alliance management. Tho has held strategic leadership and management roles with emphasis on increasing performance, economics, and governance. In addition, Tho is an active speaker and blogger on analytics and data management.

Table of Contents

Foreword xi

Acknowledgments xv

About the Author xvii

Introduction xix

Chapter 1 The Analytical Data Life Cycle 1

Stage 1: Data Exploration 2

Stage 2: Data Preparation 3

Stage 3: Model Development 4

Stage 4: Model Deployment 6

End-to-End Process 8

Chapter 2 In-Database Processing 11

Background 12

Traditional Approach 13

In-Database Approach 15

The Need for In-Database Analytics 16

Success Stories and Use Cases 18

In-Database Data Quality 35

Investment for In-Database Processing 44

Endnotes 47

Chapter 3 In-Memory Analytics 49

Background 50

Traditional Approach 51

In-Memory Analytics Approach 53

The Need for In-Memory Analytics 56

Success Stories and Use Cases 65

Investment for In-Memory Analytics 80

Chapter 4 Hadoop 83

Background 84

Hadoop in the Big Data Environment 86

Use Cases for Hadoop 87

Hadoop Architecture 89

Best Practices 92

Benefits of Hadoop 95

Use Cases and Success Stories 97

A Collection of Use Cases 103

Endnote 105

Chapter 5 Bringing It All Together 107

Background 108

Collaborative Data Architecture 109

Scenarios for the Collaborative Data Architecture 113

How In-Database, In-Memory, and Hadoop Are

Complementary in a Collaborative Data Architecture 119

Use Cases and Customer Success Stories 122

Investment and Costs 150

Endnotes 151

Chapter 6 Final Thoughts and Conclusion 153

Five Focus Areas 154

Cloud Computing 157

Security: Cyber, Data Breach 168

Automating Prescriptive Analytics: IoT, Events, and Data Streams 179

Cognitive Analytics 188

Anything as a Service (XaaS) 197

Conclusion 204

Afterword 208

Index 210