Preparing for your Professional Data Engineer Journey
Earned Dec 30, 2025 EST
在 BigQuery 使用 Gemini 模型
Earned Dec 26, 2025 EST
Build Streaming Data Pipelines on Google Cloud
Earned Dec 23, 2025 EST
透過 Gemini in BigQuery 提升工作效率
Earned Dec 22, 2025 EST
Serverless Data Processing with Dataflow: Develop Pipelines
Earned Dec 22, 2025 EST
使用 Dataplex 建構資料網格
Earned Dec 3, 2025 EST
透過 BigQuery 建構資料倉儲
Earned Dec 2, 2025 EST
Serverless Data Processing with Dataflow: Operations
Earned Dec 1, 2025 EST
Serverless Data Processing with Dataflow: Foundations
Earned Nov 29, 2025 EST
Build Batch Data Pipelines on Google Cloud
Earned Nov 27, 2025 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned Nov 25, 2025 EST
從 BigQuery 資料取得深入分析結果
Earned Nov 18, 2025 EST
Google Cloud 中的資料工程簡介
Earned Oct 19, 2025 EDT
Google Cloud: Prompt Engineering Guide
Earned Jul 25, 2025 EDT
在 Google Cloud 部署 Kubernetes 應用程式
Earned Jun 11, 2025 EDT
在 Google Cloud 實作 Cloud 安全防護措施：基礎知識
Earned Jun 11, 2025 EDT
建構安全的 Google Cloud 網路
Earned Apr 27, 2025 EDT
重要的 Google Cloud 基礎架構：核心服務
Earned Apr 27, 2025 EDT
在 Google Cloud 設定應用程式開發環境
Earned Apr 16, 2025 EDT
重要的 Google Cloud 基礎架構：基本概念
Earned Apr 14, 2025 EDT
Google Cloud 必備知識
Earned Mar 15, 2025 EDT
Google Cloud 基礎知識：核心基礎架構
Earned Feb 26, 2025 EST
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.
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.
了解详情
本課程會說明 Gemini in BigQuery，這是一套由 AI 輔助的功能，可協助「從資料到 AI」的工作流程。這些功能包含資料探索和準備、程式碼生成和疑難排解，以及工作流程探索和視覺化。本課程將透過概念解說、應用實例和實作實驗室，協助資料從業人員提升工作效率，並加速開發 pipeline。
了解详情
In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.
了解详情
完成「使用 Dataplex 建構資料網格」技能徽章入門課程，即可證明您具備下列技能：使用 Dataplex 建構資料網格， 以利在 Google Cloud 維護資料安全性，並協助治理和探索資料。您將練習並測試自己的技能，包括在 Dataplex 為資產加上標記、指派 IAM 角色，以及評估資料品質。
In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.
了解详情
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.
了解详情
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.
了解详情
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.
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。
了解详情
Google Cloud : Prompt Engineering Guide examines generative AI tools, how they work. We'll explore how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses.
Preparing for your Professional Data Engineer Journey
Earned Dec 30, 2025 EST
在 BigQuery 使用 Gemini 模型
Earned Dec 26, 2025 EST
Build Streaming Data Pipelines on Google Cloud
Earned Dec 23, 2025 EST
透過 Gemini in BigQuery 提升工作效率
Earned Dec 22, 2025 EST
Serverless Data Processing with Dataflow: Develop Pipelines
Earned Dec 22, 2025 EST
使用 Dataplex 建構資料網格
Earned Dec 3, 2025 EST
透過 BigQuery 建構資料倉儲
Earned Dec 2, 2025 EST
Serverless Data Processing with Dataflow: Operations
Earned Dec 1, 2025 EST
Serverless Data Processing with Dataflow: Foundations
Earned Nov 29, 2025 EST
Build Batch Data Pipelines on Google Cloud
Earned Nov 27, 2025 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned Nov 25, 2025 EST
從 BigQuery 資料取得深入分析結果
Earned Nov 18, 2025 EST
Google Cloud 中的資料工程簡介
Earned Oct 19, 2025 EDT
Google Cloud: Prompt Engineering Guide
Earned Jul 25, 2025 EDT
在 Google Cloud 部署 Kubernetes 應用程式
Earned Jun 11, 2025 EDT
在 Google Cloud 實作 Cloud 安全防護措施：基礎知識
Earned Jun 11, 2025 EDT
建構安全的 Google Cloud 網路
Earned Apr 27, 2025 EDT
重要的 Google Cloud 基礎架構：核心服務
Earned Apr 27, 2025 EDT
在 Google Cloud 設定應用程式開發環境
Earned Apr 16, 2025 EDT
重要的 Google Cloud 基礎架構：基本概念
Earned Apr 14, 2025 EDT
Google Cloud 必備知識
Earned Mar 15, 2025 EDT
Google Cloud 基礎知識：核心基礎架構
Earned Feb 26, 2025 EST