CHAPTER
1
An Overview of
1
Business
Intelligence,
Analytics, and Data
Science
Learning Objectives for Chapter 1
Understand today’s turbulent business environment and describe how organizations
survive and even excel in such an environment (solving problems and exploiting
opportunities)
Understand the need for computerized support of managerial decision making
Recognize the evolution of such computerized support to the current state—
analytics/data science
Describe the business intelligence (BI) methodology and concepts
Understand the various types of analytics, and see selected applications
Understand the analytics ecosystem to identify various key players and career
opportunities
1
Copyright © 2018 Pearson Education, Inc.
,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.
This book is about using business analytics as computerized support 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. This book presents the fundamentals of the techniques and the manner in
which these systems are constructed and used. We follow an EEE approach to
introducing these topics: Exposure, Experience, and Explore. The book primarily
provides exposure to various analytics techniques and their applications. The idea is that
a student will be inspired to learn from how other organizations have employed analytics
to make decisions or to gain a competitive edge. We believe that such exposure to what is
being done with analytics and how it can be achieved is the key component of learning
about analytics. In describing the techniques, we also introduce specific software tools
that can be used for developing such applications. The book is not limited to any one
software tool, so the 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.
This introductory chapter provides an introduction to analytics as well as an
overview of the book. The chapter has the following sections:
CHAPTER OUTLINE
1.1 Opening Vignette: Sports Analytics—An Exciting Frontier for Learning and
Understanding Applications of Analytics
1.2 Changing Business Environments and Evolving Needs for Decision Support and
Analytics
1.3 Evolution of Computerized Decision Support to Analytics/Data Science
1.4 A Framework for Business Intelligence
1.5 Analytics Overview
2
Copyright © 2018 Pearson Education, Inc.
, 1.6 Analytics Examples in Selected Domains
1.7 A Brief Introduction to Big Data Analytics
1.8 An Overview of the Analytics Ecosystem
1.9 Plan of the Book
1.10 Resources, Links, and the Teradata University Network Connection
TEACHING TIPS/ADDITIONAL INFORMATION
The purpose of any introductory chapter is to motivate students to be interested in the
remainder of the course (and book). The real-life cases, beginning with Magpie Sensing
and continuing with the others, will show students that business intelligence is not just an
academic subject; it is something real companies use that makes a noticeable difference
to their bottom line. So, try to relate the subject matter to these cases. For example,
consider the types of actions managers take to counter pressures, especially the list of
organizational responses. The opening case about Magpie illustrates several of the
options available to health care companies, such as innovation, partnerships with others
in the cold chain, and the use of IT to improve data access. The other cases in the chapter
offer other examples of managerial actions taken in response to pressure. By referring
back to this list when discussing other cases, you demonstrate the unity of the analytics
field.
All this should show students that a new professional who understands how information
systems can support decision making, and can help his or her employer obtain those
benefits, has a bright career path. Since students in this course are typically within a year
of graduation, that will get their attention!
3
Copyright © 2018 Pearson Education, Inc.
1
An Overview of
1
Business
Intelligence,
Analytics, and Data
Science
Learning Objectives for Chapter 1
Understand today’s turbulent business environment and describe how organizations
survive and even excel in such an environment (solving problems and exploiting
opportunities)
Understand the need for computerized support of managerial decision making
Recognize the evolution of such computerized support to the current state—
analytics/data science
Describe the business intelligence (BI) methodology and concepts
Understand the various types of analytics, and see selected applications
Understand the analytics ecosystem to identify various key players and career
opportunities
1
Copyright © 2018 Pearson Education, Inc.
,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.
This book is about using business analytics as computerized support 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. This book presents the fundamentals of the techniques and the manner in
which these systems are constructed and used. We follow an EEE approach to
introducing these topics: Exposure, Experience, and Explore. The book primarily
provides exposure to various analytics techniques and their applications. The idea is that
a student will be inspired to learn from how other organizations have employed analytics
to make decisions or to gain a competitive edge. We believe that such exposure to what is
being done with analytics and how it can be achieved is the key component of learning
about analytics. In describing the techniques, we also introduce specific software tools
that can be used for developing such applications. The book is not limited to any one
software tool, so the 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.
This introductory chapter provides an introduction to analytics as well as an
overview of the book. The chapter has the following sections:
CHAPTER OUTLINE
1.1 Opening Vignette: Sports Analytics—An Exciting Frontier for Learning and
Understanding Applications of Analytics
1.2 Changing Business Environments and Evolving Needs for Decision Support and
Analytics
1.3 Evolution of Computerized Decision Support to Analytics/Data Science
1.4 A Framework for Business Intelligence
1.5 Analytics Overview
2
Copyright © 2018 Pearson Education, Inc.
, 1.6 Analytics Examples in Selected Domains
1.7 A Brief Introduction to Big Data Analytics
1.8 An Overview of the Analytics Ecosystem
1.9 Plan of the Book
1.10 Resources, Links, and the Teradata University Network Connection
TEACHING TIPS/ADDITIONAL INFORMATION
The purpose of any introductory chapter is to motivate students to be interested in the
remainder of the course (and book). The real-life cases, beginning with Magpie Sensing
and continuing with the others, will show students that business intelligence is not just an
academic subject; it is something real companies use that makes a noticeable difference
to their bottom line. So, try to relate the subject matter to these cases. For example,
consider the types of actions managers take to counter pressures, especially the list of
organizational responses. The opening case about Magpie illustrates several of the
options available to health care companies, such as innovation, partnerships with others
in the cold chain, and the use of IT to improve data access. The other cases in the chapter
offer other examples of managerial actions taken in response to pressure. By referring
back to this list when discussing other cases, you demonstrate the unity of the analytics
field.
All this should show students that a new professional who understands how information
systems can support decision making, and can help his or her employer obtain those
benefits, has a bright career path. Since students in this course are typically within a year
of graduation, that will get their attention!
3
Copyright © 2018 Pearson Education, Inc.
