Data Lake Modernization on Google Cloud: Cloud Composer
Earned Jun 4, 2025 EDT
Preparing for your Professional Data Engineer Journey
Earned Jun 3, 2025 EDT
在 BigQuery 使用 Gemini 模型
Earned Jun 2, 2025 EDT
透過 Gemini in BigQuery 提升工作效率
Earned May 30, 2025 EDT
使用 Dataplex 建構資料網格
Earned May 30, 2025 EDT
透過 BigQuery 建構資料倉儲
Earned May 29, 2025 EDT
Serverless Data Processing with Dataflow: Foundations
Earned May 20, 2025 EDT
Build Streaming Data Pipelines on Google Cloud
Earned May 20, 2025 EDT
Build Batch Data Pipelines on Google Cloud
Earned May 19, 2025 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned May 16, 2025 EDT
Google Cloud 中的資料工程簡介
Earned May 8, 2025 EDT
Google Cloud 基礎知識：核心基礎架構
Earned May 6, 2025 EDT
Welcome to Cloud Composer, where we discuss how to orchestrate data lake workflows with Cloud Composer.
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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 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.
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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.
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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.
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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.
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在本課程中，您會學到 Google Cloud 上的資料工程、資料工程師的角色與職責，以及這些內容如何對應至 Google Cloud 提供的服務。您也將瞭解處理資料工程難題的許多方法。
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「Google Cloud 基礎知識：核心基礎架構」介紹了在使用 Google Cloud 時會遇到的重要概念和術語。本課程會透過影片和實作實驗室，介紹並比較 Google Cloud 的多種運算和儲存服務，同時提供重要的資源和政策管理工具。
Data Lake Modernization on Google Cloud: Cloud Composer
Earned Jun 4, 2025 EDT
Preparing for your Professional Data Engineer Journey
Earned Jun 3, 2025 EDT
在 BigQuery 使用 Gemini 模型
Earned Jun 2, 2025 EDT
透過 Gemini in BigQuery 提升工作效率
Earned May 30, 2025 EDT
使用 Dataplex 建構資料網格
Earned May 30, 2025 EDT
透過 BigQuery 建構資料倉儲
Earned May 29, 2025 EDT
Serverless Data Processing with Dataflow: Foundations
Earned May 20, 2025 EDT
Build Streaming Data Pipelines on Google Cloud
Earned May 20, 2025 EDT
Build Batch Data Pipelines on Google Cloud
Earned May 19, 2025 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned May 16, 2025 EDT
Google Cloud 中的資料工程簡介
Earned May 8, 2025 EDT
Google Cloud 基礎知識：核心基礎架構
Earned May 6, 2025 EDT