Build Data Lakes and Data Warehouses on Google Cloud

Overview

Build modern data lakehouses on Google Cloud using BigQuery, Cloud Storage, Apache Iceberg, BigLake, federated queries, and data governance tools.

Learn to build modern data lakehouses on Google Cloud. This course covers data lake and data warehouse architectures, the lakehouse approach with Cloud Storage and BigQuery, Apache Iceberg open table format, BigLake, federated queries, partitioning, clustering, data governance, and machine learning on the lakehouse.

Syllabus

Course introduction

Introduce the learner to the topics that will be covered in the course and the skills they will learn.

Introduction to Modern Data Engineering on Google Cloud

This module introduces the foundational concepts of data lakes and data warehouses, setting the stage for modern architectures on Google Cloud.

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

This module details the concept of a lakehouse and introduces the Google Cloud products most commonly used to build a modern data lakehouse using open-source formats.

Modernizing Data Warehouses with BigQuery and BigLake

This module explores BigQuery as the cornerstone of a modern data warehouse and introduces BigLake for unifying access across the data lake and warehouse.

Advanced Lakehouse Patterns and Data Governance

This module focuses on advanced architectural patterns for the lakehouse, including data processing, orchestration, and comprehensive data governance across BigQuery, Cloud Storage, and BigLake.

Labs and Best Practices

This module provides labs to deepen skills in the tools and technologies used by a lakehouse on Google Cloud and an overview of best practices, common mistakes, and future trends

Course Summary

Summarize the architectural and operational capabilities of the BigQuery-centric data lakehouse, covering governance, advanced analytics, and machine learning