CS5483 Data Warehousing and Data Mining

Course Aims & Objectives: This course aims to introduce students to a new frontier in database technology, "data warehousing and data mining", by studying their principles, algorithms, implementation methodology, and applications. It will analyze the components of a data warehouse, including data source and transformation tools, metadata management, query reporting and OLAP; provide a comprehensive introduction to data mining, including data selection, cleaning, coding, using different pattern recognition techniques, and reporting; and introduce students to the applications of data warehousing and data mining by using commercial tools for creating business applications. Upon completion, students should be able to (1) design and build a data warehouse by using star schema for OLAP decision support systems; (2) extract and consolidate data from various database sources for populating the warehouse; (3) understand decision trees, neural networks, clustering, nearest neighbor, fuzzy logic, genetic algorithms, and rule induction techniques in data mining; (4) apply easy-to-use and understandable techniques of data mining to address some well-defined problems from business domain. Units: 3 Level: P5 Medium of Instruction:  English  Keyword Syllabus: Data extraction, data cleansing, data transformation, metadata, on-line analytical processing (OLAP), star schema, decision trees, neutral networks, nearest neighbor and clustering, genetic algorithms, rule induction, data visualization, knowledge discovery in database. Teaching Pattern: Duration of course: 1 semester Current mix of lecture/tutorial/laboratory, other: 2 hrs. lecture; 1 hr. tutorial Assessment Pattern: Examination duration: 2 hours Percentage distribution of marks for coursework, examination, other: 50% CW; 50% Exam Grading pattern: Standard (A+AA-...F) For a student to pass the course, at least 30% of the maximum mark for the examination must be obtained.  Pre-requisite(s): Nil Pre-cursor(s): CS3402 /or CS5481 /or equivalent  Equivalent Course(s): Nil