Course Outline Ch 2 Essays

5944 Words Mar 2nd, 2012 24 Pages
CHAPTER 2: DATA WAREHOUSING Objectives: After completing this chapter, you should be able to: 1. Understand the basic definitions and concepts of data warehouses 2. Understand data warehousing architectures 3. Describe the processes used in developing and managing data warehouses 4. Explain data warehousing operations 5. Explain the role of data warehouses in decision support 6. Explain data integration and the extraction, transformation, and load (ETL) processes 7. Describe real-time (active) data warehousing 8. Understand data warehouse administration and security issues CHAPTER OVERVIEW Data warehousing is at the foundation of most BI. This is the data warehousing chapter of the book. Later chapters will use it as they discuss DW …show more content…
Benefits:

1. Microsoft BI solution is flexible and self-service. Users choose what they want to extract and manipulate. 2. Information is more accurate because of the analytical capabilities. 3. Saves time. 4. Saves money by having accurate and daily “Big Picture” of the analyzed data showing the KPI’s (key performance indicators) of their targets. 5. BI has helped their bottom line: a. Senior management understands the customer better. b. Company is more agile in making changes to the customers’ needs. c. Solution allowed them more insight in the efficiencies of the individual divisions on the company. 1. Watch and take notes on Enterprise Rental 2009 Video on Moodle (DW is built by Teradata Corp) (6:35 minutes)

II.

Data Warehousing Definitions and Concept (Section 2.1, page 32) A. Introduction: Data are sometimes incomplete and disjointed so that managers often make decisions with

partial information. Storing data in a warehouse allows for accessing and integrating pertinent data in a form that is consistent, reliable, timely, and readily available for operational decision making (Example: CDC, Hepatitis Surveillance Data. Epidemiologists obtained survey data where subjects answer questions about behaviors/risk factors pertinent to hepatitis infection; lab technicians had data on several lab markers for each patient believed to be infected. These data were not on the same system; therefore, additional manual work was necessary to merge

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