Fifteen years ago, edge companies began to revolutionize their business with advanced analytics. Now those analytics capabilities are table stakes. But the problems analytics were supposed to solve remain: * Intelligence is fractured and inconsistent across the enterprise * Agility is difficult to achieve while maintaining growth * Costs are too high and difficult to control * Data value and potential is difficult to unlock New technologies hold new promise, but they are simply more tools in an ever-growing box. They are only as effective as those who wield them. Throughout the author's…mehr
Fifteen years ago, edge companies began to revolutionize their business with advanced analytics. Now those analytics capabilities are table stakes. But the problems analytics were supposed to solve remain: * Intelligence is fractured and inconsistent across the enterprise * Agility is difficult to achieve while maintaining growth * Costs are too high and difficult to control * Data value and potential is difficult to unlock New technologies hold new promise, but they are simply more tools in an ever-growing box. They are only as effective as those who wield them. Throughout the author's 20Thus, this book. It is not prescriptive. There is no methodology, no rubric, or framework. There is no magic solution, no one thing that must be done. Rather, it is a reflection on lessons learned--from successes and failures--on how companies can transform analytics from tools they use, to a philosophy that makes knowledge and analysis pervasive and helps them define who they are now, and who they will become.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Anu Jain joined Teradata in 2017 and is responsible for leading the Americas Think Big Organization. His focus is on creating enhanced business outcomes through tailored solution delivery. He is a seasoned services and sales leader with over 20 years of experience in technology consulting organizations. Prior to Teradata, Anu led the Media, Entertainment and Cable industry segment for IBM; a $1.5 billion plus P&L. Anu was also the cofounder of Janus, a Tax & Treasury Analytics Solutions business with Agile analytics and Big Data Solutions for the Office of the CFO. Prior to Janus, Anu was a Leader at Deloitte leading their Business Intelligence and IM practices as well as serving as the Chief People Officer of their Technology Services business in North America. He has a BS in Operations Industrial Engineering from The Georgia Institute of Technology.
Inhaltsangabe
Preface vii Acknowledgments ix Introduction 1 Part I Strategies to Make Intelligence Pervasive 5 Chapter 1 Achieving High-Impact Outcomes-An Overview 9 The Right Data 11 The Right Technical Architecture and Environment 13 Operational Excellence 14 Driving High-Impact Outcomes with Pervasive Intelligence 15 Chapter 2 New Metrics for Intelligence-Information Yield 17 Information Yield-The Journey from 2D to 3D in Analytics 19 Three Foundational Steps to Drive Transformation 20 Big Data and its Impact on Information Yield 22 Information Yield and Pervasive Intelligence 24 Chapter 3 The Cloud-The Foundation for Pervasive Intelligence 25 Clouds-What's Best for You? 26 Choosing the Right Vendor Partner to Help You Fulfill the Promise of the Cloud 27 The Cloud-Not Optional for Pervasive Intelligence 29 Chapter 4 Perpetual Connectivity-Digital Supply Networks 31 DSNs Defined 32 DSNs-What They Can Do for You 32 DSN Challenges 33 The Benefi ts of a DSN Illustrated 34 DSNs and the Realization of Pervasive Intelligence 36 Chapter 5 Intelligence Analytics and Cognitive Design-The Human Factor in Pervasive Intelligence 37 Why Cognitive Design? 39 Putting It Together 46 Cognitive Design-The Human Factor in Pervasive Intelligence 46 Chapter 6 You Are Only as Good as Your Data 47 Consolidate Data 49 Secure and Govern 49 The Rising Need for a Chief Data Officer 49 Pervasive Intelligence and Data Governance 51 Chapter 7 The Data Security Awakening 53 Data Security: A Question of Managing Risk 54 Pervasive Intelligence and Data Security 59 Part II Technology to Achieve Pervasive Intelligence 61 Chapter 8 The Evolution of Data Lakes as a Fundamental Part of a New Ecosystem Architecture 63 Changes in Data Dictate Changes in Storage Technology 64 Data Lakes and Pervasive Intelligence 67 Chapter 9 Artifi cial Intelligence and Machine Learning-The Future of Pervasive Intelligence 69 The Power of (Artificial) Intelligence 70 AI in Practice 72 Machine Learning-The Star of Artificial Intelligence 74 Optimizing Machine Learning Efforts 78 AI and Pervasive Intelligence 80 Chapter 10 Analytics Operations to Enable Pervasive Intelligence 81 Operationalizing Analytics 82 Embedding AnalyticOps Throughout the Organization 86 Chapter 11 Intelligent Clouds-Combining the Cloud and Analytics to Realize Pervasive Intelligence 91 The Intelligent Cloud 92 The Benefits of Intelligence 92 Pervasive Intelligence via the Intelligent Cloud 94 Conclusion 95 Index 97
Preface vii Acknowledgments ix Introduction 1 Part I Strategies to Make Intelligence Pervasive 5 Chapter 1 Achieving High-Impact Outcomes-An Overview 9 The Right Data 11 The Right Technical Architecture and Environment 13 Operational Excellence 14 Driving High-Impact Outcomes with Pervasive Intelligence 15 Chapter 2 New Metrics for Intelligence-Information Yield 17 Information Yield-The Journey from 2D to 3D in Analytics 19 Three Foundational Steps to Drive Transformation 20 Big Data and its Impact on Information Yield 22 Information Yield and Pervasive Intelligence 24 Chapter 3 The Cloud-The Foundation for Pervasive Intelligence 25 Clouds-What's Best for You? 26 Choosing the Right Vendor Partner to Help You Fulfill the Promise of the Cloud 27 The Cloud-Not Optional for Pervasive Intelligence 29 Chapter 4 Perpetual Connectivity-Digital Supply Networks 31 DSNs Defined 32 DSNs-What They Can Do for You 32 DSN Challenges 33 The Benefi ts of a DSN Illustrated 34 DSNs and the Realization of Pervasive Intelligence 36 Chapter 5 Intelligence Analytics and Cognitive Design-The Human Factor in Pervasive Intelligence 37 Why Cognitive Design? 39 Putting It Together 46 Cognitive Design-The Human Factor in Pervasive Intelligence 46 Chapter 6 You Are Only as Good as Your Data 47 Consolidate Data 49 Secure and Govern 49 The Rising Need for a Chief Data Officer 49 Pervasive Intelligence and Data Governance 51 Chapter 7 The Data Security Awakening 53 Data Security: A Question of Managing Risk 54 Pervasive Intelligence and Data Security 59 Part II Technology to Achieve Pervasive Intelligence 61 Chapter 8 The Evolution of Data Lakes as a Fundamental Part of a New Ecosystem Architecture 63 Changes in Data Dictate Changes in Storage Technology 64 Data Lakes and Pervasive Intelligence 67 Chapter 9 Artifi cial Intelligence and Machine Learning-The Future of Pervasive Intelligence 69 The Power of (Artificial) Intelligence 70 AI in Practice 72 Machine Learning-The Star of Artificial Intelligence 74 Optimizing Machine Learning Efforts 78 AI and Pervasive Intelligence 80 Chapter 10 Analytics Operations to Enable Pervasive Intelligence 81 Operationalizing Analytics 82 Embedding AnalyticOps Throughout the Organization 86 Chapter 11 Intelligent Clouds-Combining the Cloud and Analytics to Realize Pervasive Intelligence 91 The Intelligent Cloud 92 The Benefits of Intelligence 92 Pervasive Intelligence via the Intelligent Cloud 94 Conclusion 95 Index 97
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