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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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.
運用 Gemini Code Assist 簡化應用程式開發作業
Earned Apr 12, 2026 EDT
搭配使用 API 和 Cloud Storage
Earned Apr 11, 2026 EDT
使用 Gemini 和 Streamlit 開發生成式 AI 應用程式
Earned Apr 11, 2026 EDT
使用 Gemini：雲端架構師
Earned Apr 6, 2026 EDT
部署多代理架構
Earned Apr 6, 2026 EDT
為 Google Cloud 設定服務帳戶和 IAM 角色
Earned Apr 6, 2026 EDT
使用 Document AI 大規模自動擷取資料
Earned Apr 5, 2026 EDT
Google Cloud Compute 基本操作
Earned Mar 22, 2026 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Aug 4, 2025 EDT
Google Cloud 中的資料工程簡介
Earned Aug 1, 2025 EDT
Preparing for your Professional Data Engineer Journey
Earned Jul 30, 2025 EDT