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Data Warehousing Technologies PDF

Data Warehousing Technologies
Data Warehousing Fundamentals, John Wiley & Sons

Course Description:

The Course will cover the following materials:

Data Warehouse Technologies. Data Marts. Metadata. Data warehouse Development. Architecture. Infrastructure. Platforms. Software Tools. STAR Schema. Snowflake Schema. ETL Functions. Data Quality. User Interface Features. Web-Enabled Data Warehouses. Data Mining. Physical Design. Deployment Issues. Maintenance.

Course Objectives:

· Provide a solid introduction to the topic of Data Warehousing.

· Show the difference between database and data warehousing.

· Introduce the ETL Model.

· Use the Star Schema to design a Data Warehouse.

Learning Outcomes:

After completing this course, the student should demonstrate the knowledge and ability to:

· Design a data warehouse or data mart to present information needed by management in a form that is usable for management clients.

· Implement a high quality data warehouse or data mart.

· Effectively administer a corporate data resource in such a way that it will truly meet management’s needs.

· Evaluate standards and new technologies to determine their potential impact on your information resource.

Teaching Resources:

Main Text Book:

Paulraj Ponniah, Data Warehousing Fundamentals, John Wiley & Sons, Inc. 2001. Book Web site: (Note: The book is available Online)

Supplementary Books:

  • Jiawei Han and Micheline Kamber, Data Mining: Concepts and Techniques, 2nd Ed., Morgan Kaufmann, 2006. ISBN 1-55860-901-6 Book Web site: . Note : From this Website, students can download the Original Book Slides prepared by the Authors of the Book.

· H. Liu and H. Motoda, Feature Selection for Knowledge Discovery and Data Mining, Kluwer, 1998.

Evaluation Plan:

Students will be evaluated in this course using a combination of assessment methods, including Written Exams: First Exam: 20 Marks, Second Exam : 20 , Final Exam: 40 Marks Assignments and Project : 20 Marks

Course Plan: Get the PDF version of the Course Syllabus Week 1 : Introduction : The Compelling Need for Data Warehousing (Get Slides)

· Course Description · Introduction to Data Warehouse and Data Warehousing · Date Warehousing and Data Mining · The Heart and aim of Data Warehousing · A short history of Date Warehousing

Week 2: Data Warehouse: The Building Blocks (Get Slides)

Week 3:

Week 4: Planning and Project Management (Get Slides)

Week 5: Defining the Business Requirements (Get Slides)

First Exam

Week 6: Requirements as the Driving Force for Data Warehousing

Week 7: The Architectural Components

Week 8: Infrastructure as the Foundation for Data Warehousing

Week 9: The Significant Role of Metadata

Week 10: Dimensional Modeling

Week 11: Data Extraction, Transformation, and Loading

Second Exam

Week 12: Data Quality and Data Warehousing and the Web

Week 13: More on Data Mining

Week 14: The Physical Design Process

Week 15: Data Warehouse Deployment and Maintenance

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