Leaders and Innovators: How Data-Driven Organizations are Winning with Analytics (Wiley and SAS Business Series)
By: Tho H. Nguyen (author), Bill Franks (author), James Taylor (foreword_author)Hardback
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.
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.
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
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- ID: 9781119232575
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