جامعة جرش
كلية تكنولوجيا المعلومات / / JerashUniversity
InformationTechnologyCollege

Course Title:Data Warehousing

Course prerequisite(s) and/or
corequisite(s): 1002441 / Course code: 1002341
Credit hours: 3 / Course Level: Third
Semester/Lecture Time:

Instructor Details

Instructor Name
/
e-mail
/
Office Hours

Course Description

Data Warehouse modeling and implementation: data extraction, cleansing, transformation and loading, data cube computation, materialized view selection, OLAPquery processing; Data Mining: fundamentals of data mining process and system architecture, relationship of data mining with data warehouse and OLAP systems, data pre-processing, mining techniques and application: association rules, mining sequence and time-series data, text mining; implementation of selected techniques.

Objectives

  • The data warehousing part of module aims to give students a good overview of the ideas and techniques which are behind recent development in the data warehousing and online analytical processing (OLAP) fields, in terms of data models, query language, conceptual design methodologies, and storage techniques .
  • Provide a solid introduction to the topic of Data Warehousing.
  • Show the difference between database and data warehousing.
  • Basic concepts on knowledge discovery in databases.
  • Concepts, model development, schema design for a data warehouse.
  • Data extraction, transformation, loading techniques for data warehousing
  • Concept description: input characterization and output analysis for data mining.

Course Contents:

Week / Topics / Topic Details / Reference (chapter) / Date
1,2 / Introduction /
  • Introduction to the course, basic statistics, probability.
  • Evolution of data management technologies, introduction to data warehousing concepts.
  • Data pre-processing, data extraction, transformation, loading processes, data cleansing algorithms
/ Chp.1
3,4,5 / models /
  • Defining subject areas, design of fact and dimension tables, data marts.
  • Online analytical processing (OLAP), roll-up, drill-down, slice, and dice operations
/ Chp.2
First Exam/ Projects Discussion
6, 7 / Data Warehousing /
  • Data Warehouse modeling
o Star model
o Snowflake
o Galaxy
  • Warehouse view
/ Chp3
8,9 / Data Warehouse Architectures /
  • Simple architecture
  • Data Marts
  • Staging
/ Chp.5
10,11,12 / Data Preprocessing /
  • Summarization
  • Cleaning
  • Integration and Transformation
  • Reduction
/ Chp7
Second Exam
13 / Unlocking the Data Asset for End Users (The Use of Business Information): /
  • Designing, Business Information Warehouses, Populating Business information Warehouses, User Access to Information, Information Data in Context.
/ Chp7
14 / Implementation / Methods for the implementation of Data Warehouse Systems / Chp8
15 / Review / Project Discussions and Presentations
Final Exam

Assessment and Grade Distribution

Assessment / Requirements / Points / Total
Assignment and Projects / 20%
Project / 15%
Presentation & Discussion / 5%
Individual Work / 80%
Attendance, Participation, Home works and short report / Chapter Homework’s, Discussions, Short Presentations / 10%
Quizzes / Unannounced Short quizzes
First Exam / Multiple Choice Questions worth 25% and Essay Questions worth 75% of exam grade. / 15%
Second Exam / Multiple Choice Questions worth 25% of and Essay Questions worth 75% of exam grade. / 15%
A Comprehensive Final examination / Multiple Choice Questions worth 25% and Essay Questions worth 75% of exam grade. / 40%
TOTAL / 100%

Teaching and Learning Methods:

  1. Interactive lectures

Interactive lectures using PowerPoint slides and available audio/visual tools in order to facilitate the teaching process and develop students understanding. Students will be invited to share their views and experience their knowledge. In addition, students will be asked to provide their feedback in regular bases.

  1. Group Projects and Presentation

A list of suggested research projects will be available at the beginning of the semester. Each student will submit a short proposal of the selected project, starting from the second week of classes. The proposal should identify the main idea, contents, time and plan, tools and applications that will be employed in the project. Once the project is approved by the instructor, the students can continue their work and will submit their project along with a 15 minutes presentation at the end of semester.

  1. Outside-classroom activities

Experts from academic and industrial institution will be invited to provide lectures on selected subjects covered within this course.

Text Book and References:

Text Book
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Paulraj Ponniah, “Data Warehousing Fundamentals”, John Wiley.
M.H. Dunham, “Data Mining Introductory and Advanced Topics”, Pearson Educatio.
[R1]
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Lecture Notes
[R2]
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Ralph Kimball, “The Data Warehouse Lifecycle toolkit”, John Wiley.
M Berry and G. Linoff, “Mastering Data Mining”, John Wiley.
W.H. Inmon, “Building the Data Warehouses”, Wiley Dreamtech.

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