789 Data Warehousing

This Course Schedule is subject to change throughout the course. Notification and appropriate adjustments to these requirements will be given in a timely manner!

Week

Subject

Reading (Ponniah)

Activity

9/7-11

Introduction: why data warehousing?

DW Basics

- architecture

- W. Inmon & R. Kimball

- data marts

Chap. 1; skim Chap 3

Chap. 2

Ø Website Search Assignment for Data Warehousing Research(Report#1)

Ø Analytical Paper(Report #2): Inmon versus Kimball

Ø Practice Exercise(PE01): Simple ER è DM

	www.kimballgroup.com
	www.inmoncif.com
	"The Data Warehouse Lifecycle Toolkit”, 2nd Edition, Kimball, et al, John Wiley & Sons, 2008.
	“Corporate Information Factory”, 2nd Edition, Inmon, et al, John Wiley & Sons, 2001
	"Building the Data Warehouse", 4th Edition, Inmon, John Wiley & Sons, 2008.

9/14-18

DW Basics (con’t.)

- MOLAP, ROLAP

- fact and dimension tables

- star and snowflake schemas

DW Design

- designing dimensions

- designing facts

- multiple fact tables

pp. 365-7; pp. 204-12; pp. 235-9

Chap. 5 (skim pp. 97-107); Chap. 10

Ø Report#1: Due 9/15

Practice Exercise(PE02): Information Packages

Ø Practice Exercise(PE03): Conforming Dimensions

Ø Lab 1: Database Creation

9/21-25

DW Design (con’t.)

- advanced dimension design

- special types of facts

Chap. 11 pp. 225-242

Ø Report#2: Due 9/22

Ø Practice Exercise(PE04): Dimensional Modeling

9/28-10/2

DW Design (con’t.)

- exercises

ETL Process

- data sources

- extraction processes

Chap. 12 pp. 257-88; skim Chap. 13

Ø Practice Exercise: Dimensional Modeling (continued)

Ø Lab 2: Data Mart Design

10/5-9

ETL Process (con’t.)

- loading data

- tools

Midterm Exam

Ø Topics: Weeks #1-4

10/12-16

Data Cleansing & Implementation

- constraints & indexes

- security basics

- multiprocessing

- etc

Chap. 18 pp. 429-52; skim Chap. 4

Ø Practice Exercise(PE05): Data Cleansing

Ø Practice Exercise(PE06): STAR Join

Ø Mini-Lectures: Implementation Topics

Ø Lab 3: Cleanse & Load

10/19-23

Dimensional Data Analysis

SQLaggregation functions

Data Mining

directed/supervised learning

undirected/unsupervised learning

Chap. 14 pp. 315-41

Chap. 15 pp. 343-74

Ø Practice Exercise(PE07): DW SQL Extensions #1

	Clustering Demo (K-means)
	Weka

10/26-30

Dimensional Data Analysis (2)

- SQL analytical functions

Summary Management

- materialized views

- query rewrite

pp. 242-9, 451

Ø Practice Exercise(PE08): DW SQL Extensions #2

Ø Final Project Specifications & Requirements

11/2-6

Management (2)

- materialized views

- query rewrite

Chap. 17

Ø Practice Exercise(PE09): DW SQL Extensions #3

11/9-13

DW Security

- database issues

- enterprise issues

- case studies

pp. 467-70

Ø Practice Activity: Case Study Reports (Report #3)

11/10 (M)

Project Defense

11/16(M) 12:30-2:30PM