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

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Product details:

• 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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