Description
Data warehouses are able to turn raw data into business intelligence that supports effective decision making and provides a competitive advantage. However, designing and building a data warehouse requires a new way of thinking and substantial investment. This overview provides a high-level introduction to data warehouse alternatives and issues.

Audience
Managers and professionals evaluating or implementing data warehouse technology.

Prerequisites
A basic understanding of relational databases is preferred.

Classroom Requirements
Overhead projector, whiteboard, flipcharts.

Format

• Presentation
  
• Written Exercises
  

Objectives
After completing this course, participants should be able to:

• Describe the business benefits of a data warehouse
• Describe different types of data warehouses
• Identify the front- and back-end components of a data warehouse
• Identify the critical success factors in designing and building a data warehouse

Introduction

Driving Forces

• Business pressures
• Technology drivers

Data Warehouse Definitions

• Why consider a data warehouse?
• What is a data warehouse?
• Benefits and risks

Data Warehouse Capabilities and Applications

• Data storage
• Operational data
• Informational systems
• Analytic systems
• Tools and their use

Data Warehouse Architecture Components

• Data warehouse elements
• Middleware
• Database engines
• Applications
• Datamarts

Data Warehouse Design and Development

• Defining requirements
• Modeling data
• Cleansing data
• Performing extraction, transformation, and loading
• Maintaining the data warehouse

Conclusion

• Critical success factors