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Data Warehousing and Data Mining IS-427 مستودعات البيانات و التنقيب عنها نال 427 استاذ المادة :ا .والء ناجي قسم نظم المعلومات كلية علوم الحاسب والمعلومات جامعة االميرة نورة بنت عبد الرحمن Course website: http://www.acadox.com/class/5367 ايميل [email protected] : 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. Topics to be discussed (theoretical content): 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. Brief description of basic learning outcomes: 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. Schedule of Assessment Tasks according to which the students are evaluated during the Semester index The nature of the evaluation function Due week Assessment weight (%) 1 First exam Week 7 20% 2 Second exam Week 12 20% 3 homework 4 Project+ Presentation 5 Final exam(Theoretical) Total: 5% During the semester After Week 15 100% 15% 40%