Data Warehouse Fundamentals

Data Warehouse Fundamentals is a foundational course that introduces students to the concepts, architecture, and techniques used in designing and managing data warehouses. The course focuses on how large volumes of data from multiple sources are collected, transformed, stored, and organized to support business intelligence and decision-making.

Students learn key concepts such as data integration, data modeling, Extract, Transform, and Load (ETL) processes, and data warehousing architectures. The course emphasizes understanding analytical data systems and how they differ from transactional databases, along with the role of data warehouses in reporting, analytics, and performance management.

Course Objectives

• Understand the fundamentals of data warehousing

• Learn data warehouse architecture and components

• Understand ETL processes and data integration

• Apply data modeling techniques for analytical systems

• Support data-driven decision-making processes

Key Topics Covered

• Introduction to Data Warehousing

• Data Warehouse Architecture

• Data Sources and Data Integration

• ETL Concepts and Tools

• Dimensional Modeling (Star and Snowflake Schemas)

• Fact and Dimension Tables

• Data Quality and Data Governance

• OLAP Concepts and Analytics

• Data Warehouse Performance and Optimization

• Introduction to Business Intelligence

Learning Outcomes

By the end of the course, students will be able to:

• Explain core data warehouse concepts and architectures

• Design basic dimensional data models

• Understand ETL workflows and data transformation processes

• Differentiate between transactional and analytical systems

• Use data warehouses to support reporting and analytics

Who Should Take This Course

• Students in Computer Science, IT, or Data Analytics

• Beginners interested in data engineering and analytics

• Professionals seeking foundational knowledge of data warehousing