Back to Business Intelligence Systems
Session 3
Business Intelligence Systems

Data Warehousing Architecture and Design

4.5 hours
Duration
8
Materials
6
Objectives
Session Overview

Comprehensive study of data warehouse architecture, design principles, ETL processes, data integration strategies, and enterprise data warehouse implementation.

Learning Objectives
By the end of this session, you should be able to:
  • Design enterprise data warehouse architecture with proper layering and staging
  • Implement Inmon and Kimball methodologies for data warehouse development
  • Master ETL (Extract, Transform, Load) processes and workflow design
  • Apply data quality management and cleansing techniques
  • Design metadata management systems and data governance frameworks
  • Implement real-time and near-real-time data integration strategies
Course Materials
Download materials for offline study and reference
Data Warehouse Architecture Guide (80 pages)
Available material
Inmon vs Kimball Methodology Comparison
Available material
ETL Design Patterns and Best Practices
Available material
Data Quality Management Framework
Available material
Metadata Management System Design
Available material
Real-time Data Integration Techniques
Available material
Enterprise Data Warehouse Implementation Project
Available material
Data Governance and Stewardship Guidelines
Available material