Jest członkiem od 2025
Data Lake Modernization on Google Cloud: Cloud Composer
Earned wrz 30, 2025 EDT
Build Batch Data Pipelines on Google Cloud
Earned wrz 29, 2025 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned wrz 23, 2025 EDT
Introduction to Data Engineering on Google Cloud
Earned wrz 18, 2025 EDT
Welcome to Cloud Composer, where we discuss how to orchestrate data lake workflows with Cloud Composer.
In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting. Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
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.
In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.