Chapter 03 – Databases and Data Warehouses: Supporting the Analytics-Driven Organization
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CHAPTER 3
DATABASES AND DATA WAREHOUSES:
SUPPORTING THE ANALYTICS-DRIVEN ORGANIZATION
JUMP TO THE SUPPORT YOU WANT
STUDENT LEARNING OUTCOMES
2. Define the five software components of a database management system.
4. Define the five major types of data-mining tools in a data warehouse environment.
CHAPTER SUMMARY
This chapter focuses on the technologies of databases, database management systems, data
warehouses, and data-mining tools.
It does so by discussing those technologies within the context of how they help organizations
organize and manage transaction information (databases and database management systems)
and business intelligence (data warehouses and data-mining tools).
The primary sections of this chapter include:
2. Database Management System Tools
4. Information Ownership
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LECTURE OUTLINE
INTRODUCTION (p. 66)
THE RELATIONAL DATABASE MODEL (p. 68)
2. Created with Logical Structures
4. With Built-In Integrity Constraints
DATABASE MANAGEMENT SYSTEM TOOLS (p. 72)
2. Data Manipulation Subsystem
4. Data Administration Subsystem
DATA WAREHOUSES AND DATA MINING (p. 79)
1. What Is a Data Warehouse?
3. The Analytics Life Cycle
5. Important Considerations in Using a Data Warehouse
INFORMATION OWNERSHIP (p. 86)
2. The Sharing of Information with Responsibility
3. Information Cleanliness
END OF CHAPTER (p. 88)
1. Summary: Student Learning Outcomes Revisited
3. Closing Case Study Two
5. Short-Answer Questions
7. Discussion Questions
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Chapter 03 – Databases and Data Warehouses: Supporting the Analytics-Driven Organization
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MODULES, PROJECTS, AND DATA FILES
Supporting Modules
XLM/C Designing Databases and Entity-Relationship Diagramming – step-by-step instructions
concerning how the design the optimal structure of a database including defining entity classes
XLM/J Implementing a Database with Microsoft Access – hands-on instructions concerning
Group Projects
• Building Value Chains: Helping Customers Define Value
Electronic Commerce Projects
• Searching job databases
• Exploring Google Earth
• Financial aid resources
Data Files
• Solomon Enterprises.mdb – for Assignment and Exercise #3 on p. 91
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Chapter 03 – Databases and Data Warehouses: Supporting the Analytics-Driven Organization
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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.
• This slide presents the graphic and information for the opening
outrageous industry transformation
• These are some great questions for class discussion
• Most of your students will have only handled music in digital form in
the past few years
• This slide provides an introduction for the chapter and defines two
important terms
• This provides an introduction to the chapter and IT tools for managing
information.
• IT tools help manage and organize information primarily through OLTP
Chapter 03 – Databases and Data Warehouses: Supporting the Analytics-Driven Organization
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• This slide presents further elaboration on the differences between
OLTP and OLAP.
• This is a good time to note that OLTP is supported primarily by
• This slide provides Figure 3.1 on page 67.
• You can use it to illustrate the differing applications of databases and
• This slide presents the organization for the chapter and the remaining
slides.
• This slide starts the section on relational databases (Student Learning
Outcome #1).
• This slide lists the common characteristics of a database, specifically
relational databases.
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• This slide presents Figure 3.2 on page 69.
• It is for Solomon Enterprises.
• This slide focuses on the fact that you define and build a database by
first defining its logical structure in a data dictionary.
• This slide presents the characteristic of logical ties within database
information.
• It defines primary and foreign keys, which are the logical ties.
• It presents Figure 3.3 on page 70 which shows all of the logical ties by
• This slide continues the discussion of logical ties within database
information.
• This slide talks about integrity constraints.
• Integrity constraints are defined within the data dictionary while
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• This slide starts the section on database management systems
(Student Learning Outcome #2).
• It provides the basic definition for a DBMS and presents Figure 3.4 on
• This slide lists the 5 components of a DBMS.
• We cover them in detail on subsequent slides.
• The first component of a DBMS is the DBMS engine, which is defined
on this slide.
• This is the least seldom recognized component of a DBMS but the one
• The second component is the data definition subsystems which is
what people use to work with a data dictionary and define the
• This slide defines the data manipulation subsystem, the third
component of a DBMS.
Chapter 03 – Databases and Data Warehouses: Supporting the Analytics-Driven Organization
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• This slide defines a view.
• It illustrates a view by presenting Figure 3.5 on page 74.
• This slide defines a report generator.
• It illustrates a report generator by presenting Figure 3.6 on page 75.
• This slide defines a QBE tool.
• It illustrates a QBE tool by presenting Figure 3.7 on page 77.
• This slide defines SQL and points out that SQL is used mostly by IT
specialists.
• This slide defines the fourth component of a DBMS – the application
generation subsystem – and points out that this subsystem is used
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• This slide defines the final component of a DBMS – the data
administration subsystem.
• This slide presents the notion of a backup and the recovery process.
• Stress how important these are in today’s information-based business
world.
• This slide briefly talks about security management, query
• This slide briefly talks about concurrency control and change
management facilities within the data administration subsystem.
• This slide starts the section on data warehouses and data mining tools
(Student Learning Outcomes #3 and #4).
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• This slide presents the characteristics of a data warehouse.
• To illustrate these, you can refer to Figure 3.8 on page 80.
• You can also build a 3-D pivot table in Excel, which will exhibit the
• This slide defines data-mining tools.
• It also lists the 5 major tools in the tool set of the analytics
• This slide presents Figure 3.9 on page 81
• It is a graphical depiction of a data warehousing environment and the
• This slide lists and provide definitions for 3 tools in the tool set of the
analytics professional
• This slide lists and provides definitions for 2 tools in the tool set of the
analytics professional
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• This slide presents Figure 3.10 on page 83
• This slide presents Figure 3.11 on page 84
• It is a graphical depiction of the analytics life cycle
• This slide defines and describes the steps within extraction,
transformation, and loading (ETL)
• This slide defines a data mart and presents Figure 3.12 on page 85,
which provides a graphical depiction of the relationship between a
• This slide presents some considerations for data warehouses
• These are important discussion topics
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• This slide presents a discussion of information ownership, learning
outcome #5
• This slide presents the definitions for four important C-level positions
in an organization that must provide strategic management support
• This slide presents a discussion of the strategic management support
needed for information as a resource.
• It also defines two fairly high-level IT positions.
• This slide talks about information ownership and sharing.
• Information is for everyone but someone must take responsibility for
• This slide talks about information cleanliness and the need for it.
Chapter 03 – Databases and Data Warehouses: Supporting the Analytics-Driven Organization
CLOSING CASES
CLOSING CASE STUDY ONE (p. 89)
WHEN MAKING A DATABASE OF PUBLIC INFORMATION AVAILABLE TO THE PUBLIC CAN BE
BAD
The two closing case studies in this chapter set in diametric opposition to each other.
This one covers when making publicly available information can be bad.
QUESTIONS
1. Let’s separate the two issues. First, law enforcement agencies frequently publish the
location to red-light camera programs and speed traps. Should that published information
be made available through an app to help drivers avoid getting a ticket? Why or why not?
2. Second, let’s consider location information for DUI checkpoints. If law enforcement
agencies publish this information, is it okay to have an app for drivers? Why or why not?
If law enforcement agencies do not publish DUI checkpoint information, is it okay to have
an app that allows drivers to enter those locations? Why or why not?
3. Many people believe that drivers should not use a smartphone at all, even for making
phone calls, while operating a vehicle. What kind of potential danger does this added
distraction create? How often do you drive and use your phone? For what purpose do
you use your phone?