How do partitioning and clustering optimize BigQuery performance and cost for a large dataset like Cymbal's sales data?
この演習はコースの一部です
理論を実践に変える、インタラクティブな演習のひとつをお試しください
Introduce the learner to the topics that will be covered in the course and the skills they will learn.
This module introduces the foundational concepts of data lakes and data warehouses, setting the stage for modern architectures on Google Cloud.
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.
This module explores BigQuery as the cornerstone of a modern data warehouse and introduces Lakehouse for unifying access across the data lake and warehouse.
現在の演習
This module focuses on advanced architectural patterns for the lakehouse, including data processing, orchestration, and comprehensive data governance across BigQuery, Cloud Storage, and Lakehouse.
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
Summarize the architectural and operational capabilities of the BigQuery-centric data lakehouse, covering governance, advanced analytics, and machine learning
