This 2-hour live, interactive session introduces you to the core principles of Data Warehousing — the foundation of all analytics and data engineering systems.
You’ll learn how data flows from source to reporting layers, how schemas are designed, and how cloud data warehouses like Azure Synapse,AWS Redshift Snowflake and Databricks Lakehouse are transforming traditional architectures - explained through industry examples from multiple sectors.
The session combines real-world examples & visual walkthroughs to help you build a solid conceptual understanding that bridges theory with practice.
🧠 What You’ll Learn
-
What is a Data Warehouse and why it matters
-
OLTP vs OLAP systems — simplified comparison
-
Core Data Warehouse layers (Staging → Integration → Presentation)
-
Star and Snowflake Schema Design
-
Kimball vs Inmon approaches — which fits where
-
Basics of ETL / ELT pipelines
-
Intro to modern cloud warehouses (Azure,AWS,GCP, Snowflake, Databricks)
-
Key governance and performance optimization principles
👥 Who Is This Class For
-
Students pursuing B.Tech, MCA, or MBA (Analytics specialization)
-
Working professionals entering Data Engineering or Analytics roles
-
Beginners who want to understand data architecture fundamentals before learning tools
-
Managers or non-technical professionals looking to understand the data ecosystem conceptually
🎯 Benefits / Learning Outcomes
-
Gain a clear conceptual foundation of data warehousing
-
Understand how modern data platforms are structured and connected
-
Learn how to interpret architecture diagrams and data models
-
Build confidence to pursue advanced courses in Data Engineering or Cloud Data Platforms
-
Receive session materials and a reference blueprint for self-study
🧩 Prerequisites
-
Basic understanding of databases (tables, queries, relationships)
-
Interest in data, analytics, or cloud computing
-
No coding or tool experience required — this session focuses on conceptual clarity and architecture understanding
Certified
You have 
