Chapter 04 – Analytics, Decision Support, and Artificial Intelligence: Brainpower for Your Business
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CHAPTER 4
ANALYTICS, DECISION SUPPORT, AND ARTIFICIAL INTELLIGENCE:
BRAINPOWER FOR YOUR BUSINESS
JUMP TO THE SUPPORT YOU WANT
STUDENT LEARNING OUTCOMES
2. Describe the decision support role of specialized analytics like predictive and text analytics.
4. Explain why neural networks are effective decision support tools.
6. Describe data-mining agents and multi-agent systems as subsets of intelligent agents and
agent-based technologies.
CHAPTER SUMMARY
This chapter focuses on the traditionally-accepted decision support that IT can provide. This
support includes decision support systems, geographic information systems, and a host of
various IA tools including neural networks, genetic algorithms, expert systems, and agent-based
technologies. New to this chapter in this edition is analytics, with a focus on predictive
analytics and test analytics.
The primary sections of this chapter include:
1. Decisions and Decision Support
3. Data-Mining Tools and Models
5. Agent-Based Technologies
Chapter 04 – Analytics, Decision Support, and Artificial Intelligence: Brainpower for Your Business
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LECTURE OUTLINE
INTRODUCTION (p.98)
DECISIONS AND DECISION SUPPORT (p. 98)
2. Decision Support Systems
GEOGRAPHIC INFORMATION SYSTEMS (p. 103)
DATA-MINING TOOLS AND MODELS (p. 104)
1. Predictive Analytics
3. Endless Analytics
ARTIFICIAL INTELLIGENCE (p. 110)
2. Neural Networks and Fuzzy Logic
AGENT-BASED TECHNOLOGIES (p. 114)
1. Intelligent Agents
END OF CHAPTER (p. 118)
1. Summary: Student Learning Outcomes Revisited
3. Closing Case Study Two
5. Short-Answer Questions
7. Discussion Questions
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Chapter 04 – Analytics, Decision Support, and Artificial Intelligence: Brainpower for Your Business
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MODULES, PROJECTS, AND DATA FILES
Supporting Modules
XLM/D Decision Analysis with Spreadsheet Software – Extended Learning Module D provides
hands-on instructions concerning how to use many of the powerful decision support features of
Group Projects
• Assessing the Value of Customer Relationship Management: Trevor Toy Auto Mechanics
• Analyzing the Value of Information: Affordable Homes Real Estate
• Executive Information System Reporting
Electronic Commerce Projects
• Best in computer statistics and resources
• Consumer information
Data Files
• There are no data files associated with this chapter. There may, however, be data files for
the Group Projects you select.
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Chapter 04 – Analytics, Decision Support, and Artificial Intelligence: Brainpower for Your Business
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• These are the Student Learning Outcomes for the chapter.
• Use them as a road map to inform your students of what you will be
covering.
• These are the Student Learning Outcomes for the chapter.
• Use them as a road map to inform your students of what you will be
• This opening case study is a good example of how those who are not
in the IT industry use and benefit from decision support
• The objective here is to underline the idea that decision support
• This is a good set of questions to cover with your students.
• You may be teaching an online or hybrid.
Chapter 04 – Analytics, Decision Support, and Artificial Intelligence: Brainpower for Your Business
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• This slide introduces the notion that “decisions” are an important part
of any business
• This slide presents the organization of the chapter
• It identifies the major sections and their associated learning outcomes
• This slide presents the four phases of decision making and describes
them
• This slide lists and defines the different types of decisions that
everyone faces
• It illustrates the interrelationships between (1) structured and
• This slide presents Figure 4.2 on page 97
Chapter 04 – Analytics, Decision Support, and Artificial Intelligence: Brainpower for Your Business
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• This slide begins the discussion of decision support systems (Student
Learning Outcome #1)
• It defines a DSS
• This slide lists and defines the three components of a DSS
• The components include:
o Model management
• This slide presents Figure 4.4 on page 102
• It defines a GIS and describes their use and role in decision making
• This slide begins the discussion of geographic information systems
(GISs)
• This slide presents Figure 4.5 on page 103
• It shows Google Earth with layers
Chapter 04 – Analytics, Decision Support, and Artificial Intelligence: Brainpower for Your Business
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• This slide presents a long list of data-mining tools and models
• The first several were covered in Chapter 3
and models
• This slide and the next describe many of the uses of data-mining tools
• This slide and the previous describe many of the uses of data-mining
tools and models
• This slide defines predictive analytics and list some of the many
applications of predictive analytics
• This slide lists and defines two important components of predictive
analytics
Chapter 04 – Analytics, Decision Support, and Artificial Intelligence: Brainpower for Your Business
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• This slide presents Figure 4.6 on page 106
• It illustrates the analytics process of a customer prediction application
• This slide presents the example in the book of building a predictive
analytics model to determine which customers are most likely to
respond to a social-media advertising campaign
• This slide defines text analytics
• It also briefly introduces the in-text text analytics example of Gaylord
• Text analytics is an interesting topic
• A lot of processing in text analytics is devoted to dissecting words and
• Text analytics is an interesting topic
• A lot of processing in text analytics is devoted to dissecting words and
• There are many specialized focuses of analytics.
• Slides #26-#28 provide the definitions for just a few of the many of
these focuses.
Chapter 04 – Analytics, Decision Support, and Artificial Intelligence: Brainpower for Your Business
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• There are many specialized focuses of analytics.
• Slides #26-#28 provide the definitions for just a few of the many of
these focuses.
• There are many specialized focuses of analytics.
• Slides #26-#28 provide the definitions for just a few of the many of
chapter
• This slide introduces the concept of artificial intelligence
• It also list the four major types of AI tools that are covered in this
• This slide begins the discussion of expert systems (Student Learning
Outcome #3)
• The traffic light example on pages 110-111 is a very effective example
for illustrating how an expert system works and how people would
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• This slide provides further discussion of expert systems
• This slide begins the discussion of neural networks and fuzzy logic
• This slide demonstrates the decision support power of neural
networks by listing what they can do.
• This slide defines and describes fuzzy logic and lists several
applications of fuzzy logic
• This slide begins the discussion of genetic algorithms (Student
Learning Outcome #5)
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• This slide presents some real world applications of genetic algorithms
• A simple Web search for genetic algorithms will yield many more
applications
• This slide further describes genetic algorithms by describing what they
can do
• This introduces and provides the definition for agent-based
technologies (Student Learning Outcome #6)
• These are among the newest of IT technologies in general and
• This slide presents Figure 4.8 on page 114
• It provides a graphical framework for agent-based technologies
• These two slides provide the definitions for the five types of agent–
based technologies
Chapter 04 – Analytics, Decision Support, and Artificial Intelligence: Brainpower for Your Business
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• These two slides provide the definitions for the five types of agent–
based technologies
• These two slides provide the definitions for the four types of
intelligent agents
• The primary focus in this chapter is on data-mining agents as an
• These two slides provide the definitions for the four types of
intelligent agents
• This slide defines biomimicry and provides how biomimicry is used in
the business world
• This slide defines and describes swarm intelligence
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SLIDE 47
• This slide presents the characteristics of swarm intelligence
Chapter 04 – Analytics, Decision Support, and Artificial Intelligence: Brainpower for Your Business
CLOSING CASES
CLOSING CASE STUDY ONE (p. 119)
Crystal Ball, Clairvoyant, Fortune Telling… Can Predictive Analytics Deliver the Future?
QUESTIONS
1. Many predictive analytic models are based on neural network technologies. What is the
role of neural networks in predictive analytics? How can neural networks help predict the
likelihood of future events. In answering these questions, specifically reference Blue Cross
Blue Shield of Tennessee.
DISCUSSION
2. What if the Richmond police began to add demographic data to its predictive analytics
system to further attempt to determine the type of person (by demographic) who would in
all likelihood commit a crime. Is predicting the type of person who would commit a crime
by demographic (ethnicity, gender, income level, and so on) good or bad?
DISCUSSION
3. In the movie Gattaca, predictive analytics were used to determine the most successful
career for a person. Based on DNA information, the system determined whether or not an
individual was able to advance through an educational track to become something like an
engineer or if the person should only complete a lower level of education and become a
janitor. The government then acted on the system’s recommendations and placed people
in various career tracks. Is this a good or bad use of technology? How is this different from
the variety of personal tests you can take that inform of your aptitude for different careers?