MET CS 699 OL-- Data Mining and Business Intelligence
Suresh Kalathur, Ph.D.
Assistant Professor, Computer Science Dept.
Boston Univeristy Metropolitan College
808 Commonwealth Ave, Room 250
Boston, MA 02215
Data mining and investigation is a key goal behind any data warehouse effort. The course provides an introduction to
concepts behind data mining, text mining, and web mining.
The course surveys various data mining applications, methodologies, techniques, and models. Topics include classification, decision trees, association rules, and clustering.
The course wraps up with data mining case studies using
large data sets taken from real-world projects.
Algorithms will be tested on data sets using the Weka
Data mining software and Microsoft SQL Server 2005
(Business Intelligence Development Studio).
The course grading will consist of analyzing a series of data mining problems, a mid term exam,
and a closed book proctored final exam.
Course Grading Policy
The course grade will be based on active class participation (10%), assignments (30%), mid term exam (30%),
and final exam(30%). Assignments are expected to be submitted by their respective
due dates. Late submission grades will be scaled with respect to the minimum grade of those submitted on time.
Data Mining: Concepts and Techniques, Second Edition,
J. Han and M. Kamber, Publisher: Morgan Kaufmann, 2006.
- Practical Business Intelligence with SQL Server 2005,
John C. Hancock and Roger Toren, Addison Wesley, 2007. , ISBN: 0-321-35698-5
- Various online materials
Student Conduct Code
Please review the academic conduct code
Tentative Course Schedule
- Module 1
- Overview of Data Mining, Data Warehousing, and Business Intelligence.
- Getting Started with SQL Server 2005 and WEKA Tools
- Module 2
- Data Preparation
- Data Warehouse and OLAP techniques
- Module 3
- Data Mining -- Classification
- Module 4
- Data Mining -- Association Analysis
- Data Mining -- Clustering
- Module 5
- Text Mining and Web Mining
- Module 6
- Real time Business Intelligence