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SRI RAMAKRISHNA INSTITUTE OF TECHNOLOGY COIMBATORE-10 (Approved by AICTE, New Delhi & Affiliated to Anna University) DEPARTMENT OF INFORMATION TECHNOLOGY Subject Code & Title Class DATA WAREHOUSING AND DATA MINING III YEAR B.TECH IT Regulation Course Prerequisite Objectives Expected Outcomes Relationship of course to program objectives Semester L P T C 3 0 0 3 VI R-2008 1. Fundamentals of Computing and Programming 2. Database Management Systems At the end of the course the student should be able 1. To know the basics of Data Warehouse & Data Mining 2. To study the methodology of databases for data warehousing & data mining to derive rules for decision support systems. Outcome a: Graduates will demonstrate an ability to apply knowledge of mathematics, science, and engineering. Outcome h: Graduates will have the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context. Outcome J: a knowledge of contemporary issues 1. Prepare students with necessary fundamentals to do their post graduate programme / Research. 2. To make the students capable of identifying problem, analyzing and providing solution based on the new technological challenges in information technology for all real world problems in their professional career. 3. To prepare the students with solid foundation in mathematics, scientific and engineering fundamentals required to solving engineering problems. Text Books: References T1. Alex Berson, Stephen J. Smith, “Data Warehousing, Data Mining, and OLAP”, Tata Mc Graw Hill Publishing Co. Ltd., New Delhi, 2008. T2. J. Han, M. Kamber, “Data Mining: Concepts and Techniques”, Harcourt India / Morgan Kauffman, New Delhi, 2001. T3. Margaret H.Dunham, “Data Mining: Introductory and Advanced Topics”, Pearson Education, New Delhi, 2004. T4. Sam Anahory, Dennis Murry, “Data Warehousing in the real world”, Pearson Education, New Delhi, 2003. Reference Books: R1. David Hand, Heikki Manila, Padhraic Symth, “Principles of Data Mining”, PHI Learning, New Delhi, 2004. R2. W.H.Inmon, “Building the Data Warehouse”, Third Edition, Wiley Publishers, NewDelhi, 2003. R3. Paulraj Ponniah, “Data Warehousing Fundamentals”, Wiley-Interscience Publication, New Delhi, 2003 Web Resources: http://nptel.iitm.ac.in/courses.php?disciplineId=106 www.web-datamining.net/data/ Mode of Evaluation Internal Assessment – 20 marks External Assessment – 80 marks Faculty T.C.EZHIL SELVAN, AP/IT COURSE PLAN 1 2 3 4 5 6 7 Unit I – INTRODUCTION & DATA WAREHOUSING Sl.No Topics to be covered as per curriculum Reference Period Introduction T1 1 Need for Data Warehouse T1 1 Paradigm Shift T1 1 Business Problem definition T1 2 Operational data Store T1 1 Informational data Store T1 1 data warehouse Architecture T1 2 Total : 9 T1 1 9 Building a Data warehouse T1 1 Mapping Data Warehouse to a Multiprocessor Architecture T1 1 T1 2 Clean up and Transformation Tools T1 2 Meta data T1 1 10 11 12 WAREHOUSING Data Warehouse Components II – DATA 8 13 Data Extraction Total : 8 Data Mining T1 1 15 Motivation, Effectiveness T1 2 Embedded data mining T1 1 Overfitting T1 1 Comparing the technologies and Encapsulation T1 2 Decision trees, Exploration Preprocessing T1 1 Prediction, Working of decision trees T1 1 Strengths and Weaknesses T1 1 16 17 18 19 20 21 III – DATA MINING 14 Total : 10 23 24 25 26 27 IV – CLUSTERING 22 Business Score Card T1 2 Nearest Neighbor prediction T1 2 Classification and Prediction T1 1 Rule Induction T1 2 Conjunctions and Disjunctions Rules vs. decision trees T1 2 28 29 30 31 32 33 34 V – RECENT TRENDS Total : 9 Multidimensional Analysis and Descriptive Mining of Complex Data Objects Spatial Databases Multimedia Databases T2 1 T2 1 T2 2 Time Series and Sequence Data T2 1 Text Databases T2 1 World Wide Web T2 1 Applications and Trends in Data Mining T2 1 Total : 9 Bridging the Curriculum Gap Case Study Description 1. Develop a Mini Project using Data Warehousing & Data Mining Concepts. STAFF HOD PRINCIPAL