1. Data Warehousing and Data Mining IS-427 مستودعات البيانات و التنقيب عنها نال 427

2. استاذ المادة: ا. ولاء ناجي قسم نظم المعلومات كلية علوم الحاسب والمعلومات جامعة الاميرة نورة بنت عبد الرحمن Course website: http://www.acadox.com/class/5367 ايميل : walaa_nagy@yahoo.comwalaa_nagy@yahoo.com

3. The principal book(s) requested:  "DATA WAREHOUSING FUNDAMENTALS: A COMPREHENSIVE GUIDE FOR IT PROFESSIONALS", by Paulraj Ponniah.  MODERN DATA WAREHOUSING, MINING, AND VISUALIZATION: CORE CONCEPTS", by George M. Marakas.  "INTRODUCTION TO DATA MINING", by Pang-Ning Tan, Michael Steinbach, and Vipin Kumar.  "DATA MINING: CONCEPTS AND TECHNIQUES", The Morgan Kaufmann Series in Data Management Systems, by Jiawei Han, and Micheline Kamber.  "DECISION SUPPORT SYSTEMS AND MEGAPUTER", by George M. Marak.  "MANAGERIAL ISSUES OF ENTERPRISE RESOURCE PLANNING SYSTEMS", by David L. Olson and David Olson.  "DATA AND TEXT MINING: A BUSINESS APPLICATIONS APPROACH", by Thomas W. Miller.

4.  Introduction to the course content, textbook(s), references and course plan.  Definition of knowledge discovery and data mining.  Fundamentals of developing and using a data warehouse, developing requirements, and designing models.  Creating a dimensional model, generating population and maintenance plans for a warehouse.  Manipulating the data in the warehouse for update, maintenance and data extraction.  The use knowledge discovery in data warehouses.  Data mining algorithms and methods including association analysis, classification, cluster analysis.  New emerging applications and trends in data mining. Topics to be discussed (theoretical content):

5. Students who successfully complete this course will be able to:  Recognize the fundamentals of data warehousing.  Manipulate the data warehousing.  Recognize the basics of data mining.  Use the knowledge discovery in data warehousing.  Conduct different methods and algorithms of data mining.  Discover knowledge in different applications. Brief description of basic learning outcomes:

6. Schedule of Assessment Tasks according to which the students are evaluated during the Semester Assessment weight (%) Due week The nature of the evaluation functionindex 20%Week 7First exam1 20%Week 12Second exam2 5%homework3 15% During the semester Project+ Presentation 4 40%After Week 15Final exam(Theoretical) 5 100%Total: