Download SRI RAMAKRISHNA INSTITUTE OF TECHNOLOGY COIMBATORE

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