Databases and Data Warehouses

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CHAPTER 3

DATABASES AND DATA WAREHOUSES
Building Business Intelligence

CONTACT INFORMATION: Stephen Haag is the primary author of this chapter. If you have any questions or comments, please direct them to him at shaag@du.edu.

THIS CHAPTER/MODULE IN SHORT FORM…

This chapter introduces your students to the vitally important role of information in an organization and the various technology tools (databases, DBMSs, data warehouses, and data-mining tools) that facilitate the management and organization of information.

In the first section – which is short but powerful – your students will learn about the value of business intelligence. We also review some key concepts such as OLTP and OLAP and introduce the notion of an operational database.

The second section is a fairly thorough (but not technical) look at the relational database model. It explores such key concepts and terms as 1. Database and relation
2. Data dictionary
3. Primary key and foreign key

The following section covers database management system software and covers key topics such as views, queries, report generators, and SQL.

In the fourth section, your students will tour data warehouses and data-mining tools that support OLAP and help create business intelligence. Within data-mining tools we cover query-and-reporting tools, intelligent agents, multidimensional analysis tools, and statistical tools.

In the final section, we look at three important issues. They are: 1. Strategic management support
2. The sharing of information with responsibility
3. Information cleanliness

STUDENT LEARNING OUTCOMES
1. Describe business intelligence and its role in an organization. 2. Differentiate between databases and data warehouses with respect to their focus on online transaction processing and online analytical processing. 3. List and describe the key characteristics of a relational database. 4. Define the five software components of a database management system. 5. List and describe the key characteristics of a data warehouse. 6. Define the four major types of data-mining tools in a data warehouse environment. 7. List key considerations in information ownership.

LECTURE OUTLINE

INTRODUCTION (p. 124)

THE RELATIONAL DATABASE MODEL (p. 126)
1. Collections of Information
2. Created with Logical Structures
3. With Logical Ties within the Information
4. With Built-In Integrity Constraints

DATABASE MANAGEMENT SYSTEM TOOLS (p. 130)
1. Data Definition Subsystem
2. Data Manipulation Subsystem
3. Application Generation Subsystem
4. Data Administration Subsystem

DATA WAREHOUSES AND DATA MINING (p. 140)
1. What Is a Data Warehouse?
2. What Are Data-Mining Tools?
3. Data Marts: Smaller Data Warehouses
4. Data Mining as a Career Opportunity
5. Important Considerations in Using a Data Warehouse

INFORMATION OWNERSHIP (p. 146)
1. Strategic Management Support
2. The Sharing of Information with Responsibility
3. Information Cleanliness

END OF CHAPTER (p. 149)
1. Summary: Student Learning Outcomes Revisited
2. Closing Case Study One
3. Closing Case Study Two
4. Key Terms and Concepts
5. Short-Answer Questions
6. Assignments and Exercises
7. Discussion Questions
8. Electronic Commerce

CORRESPONDING MODULE(S)

Extended Learning Module C – Designing Databases and Entity-Relationship Diagramming -follows this chapter. It takes your students through the process of designing a well-formed relational database. In Chapter 3, we highlight Solomon Enterprises to illustrate the use of a relational database within the context of customer relationship management. We continue with Solomon in Extended Learning Module C and focus on designing the supply chain management side.

If you choose to cover this module, we would encourage you to shortly follow with Extended Learning Module J, which teaches your students how to implement a database in Microsoft Access and build queries, reports, and forms.

GROUP PROJECTS...
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