Write a 4-6 page in-depth research paper exploring a concept you found interesting in this course (4-6contentpages). Please use at least 3 sources. A cover page is not necessary but do include aReferencespage at the end of your paper (references page does NOT count as part of your 4-6 content pages). APA format is preferred but MLA will also be accepted.ANALYTICS, DATA SCIENCE, & ARTIFICIAL INTELLIGENCE SYSTEMS FOR DECISION SUPPORT E L E V E N T H E D I T I O N Ramesh Sharda Oklahoma State University Dursun Delen Oklahoma State University Efraim Turban University of Hawaii Microsoft and/or its respective suppliers make no representations about the suitability of the information contained in the documents and related graphics published as part of the services for any purpose. All such documents and related graphics are provided “as is” without warranty of any kind. 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Library of Congress Cataloging-in-Publication Data Library of Congress Cataloging in Publication Control Number: 2018051774 http://www.pearsoned.com/permissions iii Preface xxv About the Authors xxxiv PART I Introduction to Analytics and AI 1 Chapter 1 Overview of Business Intelligence, Analytics, Data Science, and Artificial Intelligence: Systems for Decision Support 2 Chapter 2 Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications 73 Chapter 3 Nature of Data, Statistical Modeling, and Visualization 117 PART II Predictive Analytics/Machine Learning 193 Chapter 4 Data Mining Process, Methods, and Algorithms 194 Chapter 5 Machine-Learning Techniques for Predictive Analytics 251 Chapter 6 Deep Learning and Cognitive Computing 315 Chapter 7 Text Mining, Sentiment Analysis, and Social Analytics 388 PART III Prescriptive Analytics and Big Data 459 Chapter 8 Prescriptive Analytics: Optimization and Simulation 460 Chapter 9 Big Data, Cloud Computing, and Location Analytics: Concepts and Tools 509 PART IV Robotics, Social Networks, AI and IoT 579 Chapter 10 Robotics: Industrial and Consumer Applications 580 Chapter 11 Group Decision Making, Collaborative Systems, and AI Support 610 Chapter 12 Knowledge Systems: Expert Systems, Recommenders, Chatbots, Virtual Personal Assistants, and Robo Advisors 648 Chapter 13 The Internet of Things as a Platform for Intelligent Applications 687 PART V Caveats of Analytics and AI 725 Chapter 14 Implementation Issues: From Ethics and Privacy to Organizational and Societal Impacts 726 Glossary 770 Index 785 BRIEF CONTENTS iv CONTENTS Preface xxv About the Authors xxxiv PART I Introduction to Analytics and AI 1 Chapter 1 Overview of Business Intelligence, Analytics, Data Science, and Artificial Intelligence: Systems for Decision Support 2 1.1 Opening Vignette: How Intelligent Systems Work for KONE Elevators and Escalators Company 3 1.2 Changing Business Environments and Evolving Needs for Decision Support and Analytics 5 Decision-Making Process 6 The Influence of the External and Internal Environments on the Process 6 Data and Its Analysis in Decision Making 7 Technologies for Data Analysis and Decision Support 7 1.3 Decision-Making Processes and Computerized Decision Support Framework 9 Simon’s Process: Intelligence, Design, and Choice 9 The Intelligence Phase: Problem (or Opportunity) Identification 10 0 APPLICATION CASE 1.1 Making Elevators Go Faster! 11 The Design Phase 12 The Choice Phase 13 The Implementation Phase 13 The Classical Decision Support System Framework 14 A DSS Application 16 Components of a Decision Support System 18 The Data Management Subsystem 18 The Model Management Subsystem 19 0 APPLICATION CASE 1.2 SNAP DSS Helps OneNet Make Telecommunications Rate Decisions 20 The User Interface Subsystem 20 The Knowledge-Based Management Subsystem 21 1.4 Evolution of Computerized Decision Support to Business Intelligence/Analytics/Data Science 22 A Framework for Business Intelligence 25 The Architecture of BI 25 The Origins and Drivers of BI 26 Data Warehouse as a Foundation for Business Intelligence 27 Transaction Processing versus Analytic Processing 27 A Multimedia Exercise in Business Intelligence 28 Contents v 1.5 Analytics Overview 30 Descriptive Analytics 32 0 APPLICATION CASE 1.3 Silvaris Increases Business with Visual Analysis and Real-Time Reporting Capabilities 32 0 APPLICATION CASE 1.4 Siemens Reduces Cost with the Use of Data Visualization 33 Predictive Analytics 33 0 APPLICATION CASE 1.5 Analyzing Athletic Injuries 34 Prescriptive Analytics 34 0 APPLICATION CASE 1.6 A Specialty Steel Bar Company Uses Analytics to Determine Available-to-Promise Dates 35 1.6 Analytics Examples in Selected Domains 38 Sports Analytics—An Exciting Frontier for Learning and Understanding Applications of Analytics 38 Analytics Applications in Healthcare—Humana Examples 43 0 APPLICATION CASE 1.7 Image Analysis Helps Estimate Plant Cover 50 1.7 Artificial Intelligence Overview 52 What Is Artificial Intelligence? 52 The Major Benefits of AI 52 The Landscape of AI 52 0 APPLICATION CASE 1.8 AI Increases Passengers’ Comfort and Security in Airports and Borders 54 The Three Flavors of AI Decisions 55 Autonomous AI 55 Societal Impacts 56 0 APPLICATION CASE 1.9 Robots Took the Job of Camel-Racing Jockeys for Societal Benefits 58 1.8 Convergence of Analytics and AI 59 Major Differences between Analytics and AI 59 Why Combine Intelligent Systems? 60 How Convergence Can Help? 60 Big Data Is Empowering AI Technologies 60 The Convergence of AI and the IoT 61 The Convergence with Blockchain and Other Technologies 62 0 APPLICATION CASE 1.10 Amazon Go Is Open for Business 62 IBM and Microsoft Support for Intelligent Systems Convergence 63 1.9 Overview of the Analytics Ecosystem 63 1.10 Plan of the Book 65 1.11 Resources, Links, and the Teradata University Network Connection 66 Resources and Links 66 Vendors, Products, and Demos 66 Periodicals 67 The Teradata University Network Connection 67 vi Contents The Book’s Web Site 67 Chapter Highlights 67 • Key Terms 68 Questions for Discussion 68 • Exercises 69 References 70 Chapter 2 Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications 73 2.1 Opening Vignette: INRIX Solves Transportation Problems 74 2.2 Introduction to Artificial Intelligence 76 Definitions 76 Major Characteristics of AI Machines 77 Major Elements of AI 77 AI Applications 78 Major Goals of AI 78 Drivers of AI 79 Benefits of AI 79 Some Limitations of AI Machines 81 Three Flavors of AI Decisions 81 Artificial Brain 82 2.3 Human and Computer Intelligence 83 What Is Intelligence? 83 How Intelligent Is AI? 84 Measuring AI 85 0 APPLICATION CASE 2.1 How Smart Can a Vacuum Cleaner Be? 86 2.4 Major AI Technologies and Some Derivatives 87 Intelligent Agents 87 Machine Learning 88 0 APPLICATION CASE 2.2 How Machine Learning Is Improving Work in Business 89 Machine and Computer Vision 90 Robotic Systems 91 Natural Language Processing 92 Knowledge and Expert Systems and Recommenders 93 Chatbots 94 Emerging AI Technologies 94 2.5 AI Support for Decision Making 95 Some Issues and Factors in Using AI in Decision Making 96 AI Support of the Decision-Making Process 96 Automated Decision Making 97 0 APPLICATION CASE 2.3 How Companies Solve Real-World Problems Using Google’s Machine-Learning Tools 97 Conclusion 98 Contents vii 2.6 AI Applications in Accounting 99 AI in Accounting: An Overview 99 AI in Big Accounting Companies 100 Accounting Applications in Small Firms 100 0 APPLICATION CASE 2.4 How EY, Deloitte, and PwC Are Using AI 100 Job of Accountants 101 2.7 AI Applications in Financial Services 101 AI Activities in Financial Services 101 AI in Banking: An Overview 101 Illustrative AI Applications in Banking 102 Insurance Services 103 0 APPLICATION CASE 2.5 US Bank Customer Recognition and Services 104 2.8 AI in Human Resource Management (HRM) 105 AI in HRM: An Overview 105 AI in Onboarding 105 0 APPLICATION CASE 2.6 How Alexander Mann Solutions (AMS) Is Using AI to Support the Recruiting Process 106 Introducing AI to HRM Operations 106 2.9 AI in Marketing, Advertising, and CRM 107 Overview of Major Applications 107 AI Marketing Assistants in Action 108 Customer Experiences and CRM 108 0 APPLICATION CASE 2.7 Kraft Foods