COMP 300


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COMP 300

  1. 1. College of Arts and Sciences Chairperson's Application for Approval of a New Course DATE: 2/19/04 TO: CAS Academic Dean FROM: Chandra N Sekharan DEPARTMENT: Computer Science 1. PROPOSED NEW COURSE: • Course Number: COMP 300 • Credit Hours: 3 • Course Title: Data Warehousing and Data Mining • Title Abbreviation: Data Warehouse & Mining (Titles longer than 25 character positions must be abbreviated to not more than 25 character positions, exclusive of cross listing notations, for computer printouts. Count spaces and punctuation marks into total. Please limit punctuation to colons, ampersands (&), and dashes, if possible.) 2. CROSS-LISTINGS: (NOTE: All cross-listings must be approved by the chairperson(s) of the cross-listed department(s).) • Course Number: N/A • Credit Hours: N/A • Course Title: N/A • Title Abbreviation: Signature(s) of Concurring Chairperson (on original forms): Date 3. PLEASE ANSWER THE FOLLOWING REGARDING THIS PROPOSED NEW COURSE: • What, if any, will be the prerequisites for this course? COMP 251 • Will it be a prerequisite for any other course? No. • Will it be required for the major? Yes, to the newly proposed BA major • Should any course presently offered be dropped? No.
  2. 2. • Date or term in which this new course becomes effective: Fall 2004 • Which full-time faculty members will be prepared to teach or supervise this course? The course can be taught by any computer science faculty, but most notably by Chandra Sekharan, and George Thiruvathukal. • Are available material resources (e.g., library, laboratory) adequate for the course? Yes. • Are adequate resources available in the library? (Yes or No) Yes. • If no, approximate cost of obtaining sufficient resources: Signature of Bibliographer (on original form): Date • Explain briefly the writing component of this course.: Homeworks and Programming Assignments. • Has this course been offered as a special topics course? No. However, we have taught data warehousing and data mining techniques within some of our existing database classes such as COMP 251 and COMP 353. • If yes, how many times? N/A • When? N/A • What enrollment? N/A 4. REASONS FOR ADDING THIS COURSE: The course is fundamental to one of the tracks in the B.A. Computer Technology major, viz., Knowledge Databases. 5. CATALOG DESCRIPTION OF NEW COURSE: COMP 300: 3 credits: This course deals with techniques of storing of volumes of data, and building data warehouse schemas. Techniques for information retrieval such as OLAP slicing, dicing, roll-up are examined. Data mining techniques such as classification, association rules, etc. are covered using standard software packages. 6. PLEASE INCLUDE A SYLLABUS (and bibliography, if available). Attached. 7. SIGNATURES: (on original form) • Chairperson Date • Academic Council Representative Date • Academic Dean Date • Registrar's Approval of Course Number Date After approval has been given, and the course added to the Title Database, this form will be returned to the Academic Dean who will forward it to the chairperson of the initiating department. ____________________________________
  3. 3. COMP 300 Data Warehousing and Data Mining COURSE SYLLABUS Introduction Data warehousing and data mining are two major areas of exploration for knowledge discovery in databases. These topics have gained great relevance especially in the 1990’s with the web data growing at an exponential rate. As more data is collected by businesses and scientific institutions alike, knowledge exploration techniques are needed to gain useful business intelligence. This course is conceived to cover a wide spectrum of industry standard techniques using widely available database and tools software for knowledge discovery. The course teaches high volume data processing mechanisms by first building warehouse schemas such as snowflake, and star. Then OLAP query retrieval techniques are introduced. Data mining is for relatively unstructured data for which more sophisticated techniques are needed. The course aims to cover powerful data mining techniques including clustering, association rules, and classification. Learning Objectives After taking this course, students should be able to: • Understand how to store large volumes of data in a database server environment. • Use data schemas for warehouse environment. • Use OLAP queries in a data warehouse. • Know basic techniques for both directed and undirected knowledge discovery. • Know and use software package techniques for mining. • Have a good grasp of data mining techniques, such as association rules, clustering etc. Text Data Mining: Concepts and Techniques by Jiawei Han and Micheline Kamber, Morgan Kaufmann, 2000.
  4. 4. Class Participation and Attendance Student attendance is required. Hence, students are expected to arrive to class punctually. Students are expected to use software packages and hence attending computer lab sessions is a must. Grading Homework Assignments 30 points Project 10 points Midterm 20 Points Quizzes 10 Points Final Exam 30 Points Grading Scale 90-100 = A 85-89 = B+ 80-84 = B 75-79 = C+ 70-74 = C 65-69 = D 64 and lower = F Academic Integrity Students should read and understand the College of Arts and Sciences’ policy on academic integrity, which is described in the Undergraduate Studies Catalogue. Students found in violation of the policy could fail an assignment or the course and might be subjected to other penalties up to, and including, expulsion from the university.
  5. 5. Class Schedule and Readings Week Topic Week 1: Review of Databases Week 2: Applications of Data Warehousing and Data Mining Week 3: Warehouse modeling with Snowflake and Star schemas Week 4: OLAP: slicing and dicing, roll-up queries Week 5: Data Preparation Week 6: Oracle Data warehousing tools. Week 7: Data Mining primitives, Architecture +Midterm Week 8: Mining Concept description: characterization Week 9: Mining association rules Week 10 Classification and Prediction Week 11 Cluster Analysis Week 12 Introduction to Weka Software Week 13 Business Examples for Mining and Weka Week 14 Mining trends and conclusion. The class schedule closely follows the order of chapters in the text.