成为会员时间：2023
Serverless Data Processing with Dataflow: Foundations
Earned Jun 26, 2025 EDT
Preparing for your Professional Data Engineer Journey
Earned May 9, 2025 EDT
Building Codeless Pipelines on Cloud Data Fusion
Earned Jun 25, 2024 EDT
Get Started with Google Workspace Tools
Earned Dec 12, 2023 EST
This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
This quest offers hands-on practice with Cloud Data Fusion, a cloud-native, code-free, data integration platform. ETL Developers, Data Engineers and Analysts can greatly benefit from the pre-built transformations and connectors to build and deploy their pipelines without worrying about writing code. This Quest starts with a quickstart lab that familiarises learners with the Cloud Data Fusion UI. Learners then get to try running batch and realtime pipelines as well as using the built-in Wrangler plugin to perform some interesting transformations on data.
Earn an introductory skill badge by completing the Get Started with Google Workspace Tools course, where you will get introduced to Google's collaborative platform and learn to use Gmail, Calendar, Meet, Drive, Sheets, and AppSheet.