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Data Modeling & Dimensional Warehousing

Interview-ready OLTP, OLAP, and end-to-end warehouse design — from source systems to BI

Course Summary

RADE™ Data Modeling & Dimensional Warehousing for Data Engineers

This is a deep, practical data modeling and data warehousing course designed specifically for Data Engineers — not data modelers.

As a Data Engineer, you are not expected to design perfect enterprise data models from scratch.
But you are expected to:

  • Understand why data models exist

  • Know when to use OLTP vs OLAP designs

  • Clearly explain normalization vs dimensional modeling in interviews

  • Design, build, and operate real-world analytical data warehouses with confidence

This course gives you that foundation — clearly, practically, and interview-first.

What You’ll Learn

In this 5-day RADE program, you will:

  • Understand why data modeling exists and where it fits in the data engineering lifecycle

  • Clearly differentiate between:

    • OLTP systems (RDS / transactional databases)

    • OLAP systems (Redshift, Snowflake, Teradata)

Relational Modeling for OLTP Systems

  • Normalization (1NF, 2NF, 3NF)

  • Insert, update, and delete anomalies

  • Why OLTP systems are optimized for writes, not analytics

Dimensional Modeling for Analytics & Reporting

  • Facts vs dimensions

  • Star schema vs snowflake schema

  • Grain definition (the MOST important concept in modeling)

  • Surrogate keys and why they matter in data warehouses

Slowly Changing Dimensions (SCD)

  • SCD Type 1 vs Type 2 (industry-used patterns)

  • When not to use SCD and when to use snapshot fact tables instead

Data Warehouse Architecture & Data Flow

  • Staging tables, dimensions, facts, and analytical views

  • OLTP → S3 → warehouse data flow

  • ETL vs ELT

  • Incremental loads and historical tracking

End-to-End Warehousing Perspective

  • Walk through a real-world end-to-end data warehousing flow:

    • Source systems → S3 → transformations → warehouse → analytics-ready tables

  • Understand surrogate key lookups, fact loading, and analyst-facing models

Modern Data Architecture Concepts

  • Data Lakes vs Data Warehouses

  • Lakehouse architecture

  • Bronze / Silver / Gold layers

  • One Big Table (OBT): pros, cons, and real-world tradeoffs

How This Course Is Different

❌ Not academic theory
❌ Not tool-only training

✅ Designed for interviews + real-world systems
✅ Explained using business questions, not just schemas
✅ Taught from 17+ years of real industry experience

You won’t just learn what dimensional modeling is —
you’ll learn how to explain and apply it like a senior Data Engineer.

Prerequisites

  • Basic SQL (SELECT, JOIN, GROUP BY)

Outcome

By the end of this course, you’ll have:

  • Real-world clarity equivalent to years of on-the-job exposure

  • Confidence to answer any data modeling or data warehousing interview question

  • A strong foundation for advanced analytics, BI systems, and lakehouse architectures

Course Curriculum

Sachin Chandrashekhar

Lead Data Engineer @ World's #1 Airline

Course Pricing

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