Masetrs of Computer Applications:Data Mining and Data WarehouseThapar University
Price on request
Frequent Asked Questions
Recognised Bachelors degree of minimum 3 years duration in any discipline with Mathematics at least at 10+2 school level and has also qualified in the Entrance Test to be conducted by the University.OR Recognised Bachelor's Degree of minimum 3 years duration in any discipline with Mathematics as one of the subjects and has also qualified in the Entrance Test to be conducted by the University.
Discrete Mathematical Structures
Elements of Electronics Engineering
Problem Solving and Programming in C
Computer Organization and Architecture
Fundamental of Microprocessors and Interfacing
Object Oriented Programming using c++ and Java
System Analysis and Design
Statistics and Combinatorics
Data Base Management System
Design and Analysis of Algorithms
\Advanced Java and Network Programming
Computer Graphics and Multimedia
ERP and Tools
Information and Network Security
Software Project Management
Net Framework and C# Programming
System Development Project
Data Mining and Data Warehouse
Introduction: Data Warehousing, Characteristics of a Data Warehouse, Data marts and Data mining.
Developing Data Warehouse: Building a Data Warehouse, Data Warehouse architectural strategies, Design considerations, Data content , metadata, distribution of data, Tools for Data Warehousing, performance considerations, Crucial decisions in Designing a Data Warehouse, various technological considerations.
Developing Data Mart based Data warehouse: Types of Data Marts, Loading a Data Mart, Metadata for a data Mart, Data Model for a Data Mart, Maintenance of a Data Mart, Nature of Data in Data Mart, Software components for a Data Mart, Tables in Data Mart, External Data, Reference Data, Performance issues, Monitoring requirements for a Data Mart, Security in Data Mart.
OLTP and OLAP Systems: Data Modeling, Star Schema for multidimensional view, multi fact star schema, categories of OLAP tools, Managed Query Environment
Data Mining: Introduction, From Data Warehouse To Data Mining, Steps Of Data Mining Process, Types Of Data Mining Tasks, Data Mining Algorithms Viz. Classification, Association Rules And Clustering, Database Segmentation, Predictive Modeling, Link Analysis, Tools For Data Mining.
Laboratory Work: Applications of Data Warehousing and Data Mining, Case studies of Data Warehousing in Indian Railway reservation system and other industrial use.