Description

This course offers a comprehensive introduction to Data Warehousing, tailored for learners aiming to build a strong foundation in data architecture and analytics systems. Starting with the basics, such as the purpose and lifecycle of DWH, the course gradually explores key distinctions between OLTP and OLAP systems, the difference between databases, data warehouses, and data lakes, and how data marts contribute to business intelligence. The curriculum dives into core concepts like schemas (star and snowflake), fact and dimension tables—including confirmed, junk, and role-playing dimensions—and elaborates on types of fact tables and Slowly Changing Dimensions (SCD). Additionally, learners are introduced to different modeling methodologies (Kimball vs. Inmon) and the strategic role of dimensional modeling in decision-making processes. By the end of this course, students will not only grasp the theoretical constructs of Data Warehousing but will also understand practical design approaches, enabling them to support large-scale data-driven environments effectively.

Course Details