MNIT Jaipur Syllabus Information Technology Data Mining and Data Warehousing
Data Mining and Data Warehousing
Introduction to Decision Support Systems, Data Warehouse and Online Analytical Processing. Data
Warehouse Architecture: System
Processes, Process Architecture: Load Warehouse, Query, Detailed and Summarized Information.
Design: Data Base Schema Facts, Dimensions and Attributes. Introduction to Data Base and Metadata.
Data Warehouse Implementation.
Data Mining : Introduction and need.
Data Processing : Data Cleaning, Data Integration and Transformation, Data Reduction.
Data Mining Primitives : Descriptive and Predicative Data Mining, Language DMQL and its Preliminary
Clauses.Data Mining Methods: Association – Single and Multilevel, Characterization and Comparison,
Regression Analysis, Classification and Predication.
Data Mining Algorithms: Clustering, Association, Regression, Decision Trees.
OLAP : OLAP Architecture, ROLAP, and MOLAP. Application and Trends in Data Mining.
1. Data Warehousing in the Real World – Anahory and Murray, Pearson Education.
2. Data Mining – Concepts and Techniques – Jiawai Han and Micheline Kamber.
3. Building the Data Warehouse – WH Inmon, Wiley.