Modernizing Data Lakes and Data Warehouses with Google Cloud

While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.

Syllabus

Course introduction

Course Introduction

Introduction to Modern Data Engineering on Google Cloud

Module 1: Introduction to modern data engineering on Google Cloud
The classics: Data lakes and data warehouses
The modern approach: Data lakehouse
Choosing the right architecture
Data warehouses, lakes, and lakehouses concepts

Building a Data Lakehouse with Cloud Storage, Open Formats, and BigQuery

Module 2: Building a data lakehouse with Cloud Storage, open formats, and BigQuery
Building a data lake foundation
Introduction to Apache Iceberg open table format
BigQuery as the central processing engine
Combining operational data in AlloyDB
Combining operational and analytical data with federated queries
Real world use case
Data lakehouse features and benefits
Federated query with BigQuery