SECTION-A
Introduction to Data Warehousing, The need for data warehousing, Operational & Informational
Data Stores, Data Ware house Characteristics, Data Warehouse role & Structure, The cost of
warehousing data.
Introduction to OLAP & OLTP, Difference between OLAP & OLTP. OLAP Operations
SECTION-B
Building a Data Warehouse, Design/Technical/Implementation Considerations, Data Preprocessing
Overview. Data Summarization, Data Cleaning, Data Transformation, Concept
Hierarchy, Structure. Patterns & Models, Artificial Intelligence (Overview).
Multidimensional Data Model, Schemas for Multidimensional Data (Star Schema, Snowflake
Schema, Fact Constellation ), Data Warehouse Architecture, Data Warehouse Design, OLAP
Three-tier Architecture, Indexing & Querying in OLAP, OLAM, Efficient Methods of Cube
Computation, Discovery Driven Exploration of Data Cubes, Attributed-Oriented Induction.
SECTION -C
Association Rule Mining, Market Basket Analysis, Apriori Algorithm, Mining Multilevel
Association Rules, From Association Mining to Correlation Analysis, Constraint Based
Association Mining, Introduction to Classification, Classification by decision Tree, Attribute
Selection Measure.
SECTION -D
Introduction to Prediction techniques, Accuracy of a Classifier, Cross-Validation, Bootstrap,
Boosting, Bagging, Introduction to Clustering, Classification of Various Clustering Algorithms,
Selecting and Using Right DM Technique, Selecting and Using Right DM Technique, Data
Visualization.