 | Topic | Session Details | No. of Sessions |
| Introduction | -Introduction
-Data Warehousing & Data Mining as a subject
-Motivation behind data mining | 1 |
| Data Warehouse | -What is a data warehouse?
-Definition
-Multidimensional data model | |
| Data Warehouse vs Database | -Difference between Operational Database Systems and Data Warehouses
-Basic elements of the data warehouse
-Commercial Importance of data warehouse | 0.5 |
| Data Warehousing Architecture | -DW Architecture
-Enterprise Warehouse
-Data Marts
-Virtual Data Warehouse
-Metadata | 0.5 |
| Multidimensional data model | Multidimensional Representation of data
-Dimension Modeling & Hierarchy
-Lattice of Cubouds
-Summary Measures | 1 |
| OLAP Operations | -Slicing & Dicing
-Drill-up & Drill-down
-Drill within & Drill Across
-Pivot | 2 |
| Warehouse Schema | -Normalization vs Dimensional Modeling
-Star Schema, Snowflake Schema and Fact Constellation | 0.5 |
| OLAP Engine | -Specialized SQL Server
-ROLAP, MOLAP and HOLAP | 0.5 |
| Data Warehouse Implementation | -Efficient Computation of Data Cubes
-Indexing OLAP Data
-Backend Processes | 1 |
| DW Case Study 1 : Retail Sales
DW Case Study 2:
Inventory | -Retail Schema in action
-Retail Schema Extensibility
-Promotion Dimension
-Degenerate Transaction Number Dimension
-Market Basket analysis
-Inventory Periodic snapshot
-Inventory Transactions
-Inventory Accumulating Snapshot | 1 |
| DW Case Study 3:
Procurement | -Slowly Changing Dimensions (SCD)
-How to handle with SCD | 1 |
| DW Case Study 4:
CRM
DW Case Study 5:
Banking
DW Study 6: Insurance | -Large Changing Customer Dimensions
-Analyzing Customer Data from Multiple Business Processes
-Banking case study
-Insurance case study | 1 |
| Data Mining | -What is data mining
-KDD vs Data Mining
-DBMS vs DM
-DM Techniques
-DM Application Areas
-DM applications: Case Studies | 1 |
| Association Rules | -Introduction
-What is an association rule?
-Support, Confidence, and Lift paradigm
-Generalized Association Rule (Numeric,categoric,temporal,spatial etc)
-Case study on use of association rules in Market Basket Analysis and Inventory Management | 2 |
| Methods to discover association rules | -Discussion of DM algorithms (A priori, DIC, FP Tree Growth) | 1 |
| Clustering & Classification | -Definitions of clustering & classification
-Algorithms for clustering
-Case Study on clustering | 2 |
| Classification | -Decision Trees based on information entropy
-Case Study on building Decision Tree | 1 |
| Classification | -Neural Network
-Case study: Data Mining using Neural Network | 1 |
| Data Mining in soft computing paradigm | -Genetic Algorithms
-Fuzzy and Neuro Fuzzy Approaches
-Rough Set
-Support Vector Machine | 1 |
| Web Mining and Text Mining | -Web Content Mining
-Text Mining | 1 |
| | TOTAL | 20 |