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Solution Manual for Analytics, Data Science, & Artificial Intelligence Systems for Decision Support 11th by Sharda

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  • ISBN-10 ‏ : ‎ 0135192013
  • ISBN-13 ‏ : ‎ 978-0135192016
  • Author: Ramesh Sharda; Dursun Delen 

Market-leading guide to modern analytics, for better business decisions
Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organizations that have employed analytics to make decisions, while leveraging the resources of a companion website. With six new chapters, the 11th edition marks a major reorganization reflecting a new focus – analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT.

Table Of Contents:

  1. Part I Introduction to Analytics and AI
  2. Chapter 1 Overview of Business Intelligence, Analytics, Data Science, and Artificial Intelligence:
  3. 1.1 Opening Vignette: How Intelligent Systems Work for KONE Elevators and Escalators Company
  4. 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
  7. Data and Its Analysis in Decision Making
  8. Technologies for Data Analysis and Decision Support
  9. 1.3 Decision-Making Processes and Computerized Decision Support Framework
  10. Simon’s Process: Intelligence, Design, and Choice
  11. The Intelligence Phase: Problem (or Opportunity) Identification
  12. Application Case 1.1 Making Elevators Go Faster
  13. The Design Phase
  14. The Choice Phase
  15. The Implementation Phase
  16. The Classical Decision Support System Framework
  17. A DSS Application
  18. Components of a Decision Support System
  19. The Data Management Subsystem
  20. The Model Management Subsystem
  21. Application Case 1.2 SNAP DSS Helps OneNet Make Telecommunications Rate Decisions
  22. The User Interface Subsystem
  23. The Knowledge-Based Management Subsystem
  24. 1.4 Evolution of Computerized Decision Support to Business Intelligence/Analytics/Data Science
  25. A Framework for Business Intelligence
  26. The Architecture of BI
  27. The Origins and Drivers of BI
  28. Data Warehouse as a Foundation for Business Intelligence
  29. Transaction Processing versus Analytic Processing
  30. A Multimedia Exercise in Business Intelligence
  31. 1.5 Analytics Overview
  32. Descriptive Analytics
  33. Application Case 1.3 An Post and the Use of Data Visualization in Daily Postal Operations
  34. Application Case 1.4 Siemens Reduces Cost with the Use of Data Visualization
  35. Predictive Analytics
  36. Application Case 1.5 SagaDigits and the Use of Predictive Analytics
  37. Prescriptive Analytics
  38. Application Case 1.6 A Specialty Steel Bar Company Uses Analytics to Determine Available-to-Promise
  39. 1.6 Analytics Examples in Selected Domains
  40. Sports Analytics—An Exciting Frontier for Learning and Understanding Applications of Analytics
  41. Analytics Applications in Healthcare—Humana Examples
  42. Application Case 1.7 Image Analysis Helps Estimate Plant Cover
  43. 1.7 Artificial Intelligence Overview
  44. What Is Artificial Intelligence
  45. The Major Benefits of AI
  46. The Landscape of AI
  47. Application Case 1.8 AI Increases Passengers’ Comfort and Security in Airports and Borders
  48. The Three Flavors of AI Decisions
  49. Autonomous AI
  50. Societal Impacts
  51. Application Case 1.9 Robots Took the Job of Camel-Racing Jockeys for Societal Benefits
  52. 1.8 Convergence of Analytics and AI
  53. Major Differences between Analytics and AI
  54. Why Combine Intelligent Systems
  55. How Convergence Can Help
  56. Big Data Is Empowering AI Technologies
  57. The Convergence of AI and the IoT
  58. The Convergence with Blockchain and Other Technologies
  59. Application Case 1.10 Amazon Go Is Open for Business
  60. IBM and Microsoft Support for Intelligent Systems Convergence
  61. 1.9 Overview of the Analytics Ecosystem
  62. 1.10 Plan of the Book
  63. 1.11 Resources, Links, and the Teradata University Network Connection
  64. Resources and Links
  65. Vendors, Products, and Demos
  66. Periodicals
  67. The Teradata University Network Connection
  68. The Book’s Web Site
  69. Chapter Highlights
  70. Key Terms
  71. Questions for Discussion
  72. Exercises
  73. References
  74. Chapter 2 Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications
  75. 2.1 Opening Vignette: INRIX Solves Transportation Problems
  76. 2.2 Introduction to Artificial Intelligence
  77. Definitions
  78. Major Characteristics of AI Machines
  79. Major Elements of AI
  80. AI Applications
  81. Major Goals of AI
  82. Drivers of AI
  83. Benefits of AI
  84. Some Limitations of AI Machines
  85. Three Flavors of AI Decisions
  86. Artificial Brain
  87. 2.3 Human and Computer Intelligence
  88. What Is Intelligence
  89. How Intelligent Is AI
  90. Measuring AI
  91. Application Case 2.1 How Smart Can a Vacuum Cleaner Be
  92. 2.4 Major AI Technologies and Some Derivatives
  93. Intelligent Agents
  94. Machine Learning
  95. Application Case 2.2 How Machine Learning Is Improving Work in Business
  96. Machine and Computer Vision
  97. Robotic Systems
  98. Natural Language Processing
  99. Knowledge and Expert Systems and Recommenders
  100. Chatbots
  101. Emerging AI Technologies
  102. 2.5 AI Support for Decision Making
  103. Some Issues and Factors in Using AI in Decision Making
  104. AI Support of the Decision-Making Process
  105. Automated Decision Making
  106. Application Case 2.3 How Companies Solve Real-World Problems Using Google’s Machine-Learning Tools
  107. Conclusion
  108. 2.6 AI Applications in Accounting
  109. AI in Accounting: An Overview
  110. AI in Big Accounting Companies
  111. Accounting Applications in Small Firms
  112. Application Case 2.4 How EY, Deloitte, and PwC Are Using AI
  113. Job of Accountants
  114. 2.7 AI Applications in Financial Services
  115. AI Activities in Financial Services
  116. AI in Banking: An Overview
  117. Illustrative AI Applications in Banking
  118. Insurance Services
  119. Application Case 2.5 AI in China’s Financial Sector
  120. 2.8 AI in Human Resource Management (HRM)
  121. AI in HRM: An Overview
  122. AI in Onboarding
  123. Application Case 2.6 How Alexander Mann Solutions (AMS) Is Using AI to Support the Recruiting Proces
  124. Introducing AI to HRM Operations
  125. 2.9 AI in Marketing, Advertising, and CRM
  126. Overview of Major Applications
  127. AI Marketing Assistants in Action
  128. Customer Experiences and CRM
  129. Application Case 2.7 Kraft Foods Uses AI for Marketing and CRM
  130. Other Uses of AI in Marketing
  131. 2.10 AI Applications in Production-Operation Management (POM)
  132. AI in Manufacturing
  133. Implementation Model
  134. Intelligent Factories
  135. Logistics and Transportation
  136. Chapter Highlights
  137. Key Terms
  138. Questions for Discussion
  139. Exercises
  140. References

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