Mon, Nov 15, 1999
------------------------

- Introduction to Data Warehousing

- Differences between a DB and a DW

	---------------------------------------------------
	1. 	OLTP			OLAP
	2.	Day-to-Day Business	Decision Support
	3.      Relational		Multidimensional (ROLAP, MOLAP)
	4.      SQL			SQL+Aggregation+Data Analysis
	5.	Data that runs the	Data that analyzes the
	        business		business
	6.  	Changing, Incomplete	Historical, Descriptive
	7.   	Smaller			Larger (an O(M))
	8.	Transaction Throughput	Query Throughput
                is important            is important


- An example of aggregation across multiple dimensions

- Number of SELECTs needed: 2^(n-1)

- The CUBE Operator
	- The "ALL" keyword

- Format of a SELECT statement with a CUBE in it

- ROLLUP: A Restriction of the CUBE

- CUBE(ROLLUP) = CUBE

- Computing the Cube: Different Operations

- Introduction to Data Mining

Wed, Nov 17, 1999
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- Associations: Beers and Diapers

- Rules: Diapers -> Beers

- Terminology: Itemsets, Frequent Itemsets, Candidate Itemsets etc.

- Lattice Diagram induced by Subset relation

- Pruning Criterion for Frequent Itemsets

- SQL equivalent of candidate generation and frequency counting

- Breaking up associations to form rules

- Examples and Illustrations

Fri, Nov 19, 1999
------------------------

- Bank Customers Example

- Introduction to Inductive Logic Programming (ILP)

- Induction = Abduction + Justification

- Induction as reverse of deduction

- Applications of ILP

- ILP vs. Association Rules: Two Ends of a Spectrum

- Interactive Exploration
	- Kepler's Laws example