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Data Science & Artificial Intelligence Systems for Decision Support 11th Edition Ramesh Sharda Solution Manual

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Data Science & Artificial Intelligence Systems for Decision Support

Data Science & Artificial Intelligence Systems for Decision Support

  • ISBN-10 ‏ : ‎ 0135192013
  • ISBN-13 ‏ : ‎ 978-0135192016

Data Science & Artificial Intelligence Systems for Decision Support

(Solution Manual)

 

Edition: 11th Edition

Author Name: Ramesh Sharda

contact:

 

Whatsapp +1 (949) 734-4773

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Data Science & Artificial Intelligence Systems for Decision Support

Data Science & Artificial Intelligence Systems for Decision Support

  • ISBN-10 ‏ : ‎ 0135192013
  • ISBN-13 ‏ : ‎ 978-0135192016

Data Science & Artificial Intelligence Systems for Decision Support

(Solution Manual)

 

Edition: 11th Edition

Author Name: Ramesh Sharda

contact:

 

Whatsapp +1 (949) 734-4773

sample free

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Chapter 1:

An Overview of Analytics, and AI

 

 

 

 

Learning Objectives for Chapter 1

 

  • Understand the need for computerized support of managerial decision making
  • Understand the development of systems for providing decision-making support
  • Recognize the evolution of such computerized support to the current state of analytics/data science and artificial intelligence
  • Describe the business intelligence (BI) methodology and concepts
  • Understand the different types of analytics and review selected applications
  • Understand the basic concepts of artificial intelligence (AI) and see selected applications
  • Understand the analytics ecosystem to identify various key players and career opportunities

 

CHAPTER OVERVIEW

 

The business environment (climate) is constantly changing, and it is becoming more and more complex. Organizations, both private and public, are under pressures that force them to respond quickly to changing conditions and to be innovative in the way they operate. Such activities require organizations to be agile and to make frequent and quick strategic, tactical, and operational decisions, some of which are very complex. Making such decisions may require considerable amounts of relevant data, information, and knowledge. Processing these in the framework of the needed decisions must be done quickly, frequently in real time, and usually requires some computerized support. As technologies are evolving, many decisions are being automated, leading to a major impact on knowledge work and workers in many ways. This book is about using business analytics and artificial intelligence (AI) as a computerized support portfolio for managerial decision making. It concentrates on the theoretical and conceptual foundations of decision support as well as on the commercial tools and techniques that are available. The book presents the fundamentals of the techniques and the manner in which these systems are constructed and used. We follow an EEE (exposure, experience, and exploration) approach to introducing these topics. The book primarily provides exposure to various analytics/AI techniques and their applications. The idea is that students will be inspired to learn from how various organizations have employed these technologies to make decisions or to gain a competitive edge. We believe that such exposure to what is being accomplished with analytics and that how it can be achieved is the key component of learning about analytics. In describing the techniques, we also give examples of specific software tools that can be used for developing such applications. However, the book is not limited to any one software tool, so students can experience these techniques using any number of available software tools. We hope that this exposure and experience enable and motivate readers to explore the potential of these techniques in their own domain. To facilitate such exploration, we include exercises that direct the reader to Teradata University Network (TUN) and other sites that include team-oriented exercises where appropriate. In our own teaching experience, projects undertaken in the class facilitate such exploration after students have been exposed to the myriad of applications and concepts in the book and they have experienced specific software introduced by the professor. This chapter has the following sections:

 

 

CHAPTER OUTLINE

 

1.1 Opening Vignette: How Intelligent Systems Work for KONE Elevators and Escalators Company

1.2 Changing Business Environments and Evolving Needs for Decision Support and Analytics

1.3 Decision-Making Processes and Computer Decision Support Framework

1.4 Evolution of Computerized Decision Support to Business Intelligence/ Analytics/Data Science

1.5 Analytics Overview

1.6 Analytics Examples in Selected Domains

1.7 Artificial Intelligence Overview

1.8 Convergence of Analytics and AI

1.9 Overview of the Analytics Ecosystem

1.10 Plan of the Book

1.11 Resources, Links, and the Teradata University Network Connection

 

 

 

 

ANSWERS TO END OF SECTION REVIEW QUESTIONSŸ  Ÿ  Ÿ  Ÿ  Ÿ  Ÿ

 

Opening Vignette Questions

 

  1. It is said that KONE is embedding intelligence across its supply chain and enables smarter buildings. Explain.

KONE uses a variety of IoT applications to record and communicate a wide variety of systems status and performance information that can then be used to identify issues and collect important data for future applications.

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