Data Lakehouse Fundamentals

Course Overview

This course introduces the data lakehouse architecture and the open table formats that underpin it, working through what a lakehouse actually is, how it differs architecturally from a traditional data warehouse or a plain data lake, and where each approach still makes sense on its own. It’s a foundational, vendor-agnostic course: the goal is to leave you able to reason about the trade-offs between these architectures before you commit to a specific implementation.

That grounding matters because it’s a prerequisite for the more specialized data engineering courses that follow, including the Apache Iceberg and Dremio deep dives — this is where you build the conceptual map before working with a specific table format or query engine. The closing module turns theory into decision-making, walking through how to evaluate and build a lakehouse strategy for your own organization rather than adopting one by default.

What You’ll Learn

• Explain the data lakehouse architecture and how open table formats make it possible
• Compare lakehouse, data warehouse, and data lake approaches on their actual trade-offs
• Recognize when each architecture is the better fit for a given workload
• Evaluate the building blocks needed to define a lakehouse strategy for an organization

Modules

• Data Lakehouse Architecture
• Open Table Formats
• Lakehouse vs Warehouse vs Lake
• Building a Lakehouse Strategy

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