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Santhosh Muthu

Member since 2023

Bronze League

17570 points
透過 Gemini in BigQuery 提升工作效率 Earned Jan 21, 2025 EST
從 BigQuery 資料取得深入分析結果 Earned Oct 19, 2024 EDT
透過 BigQuery 建構資料倉儲 Earned Oct 18, 2024 EDT
實現 Cloud Storage 和數據保護解決方案 Earned Oct 17, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned Jan 17, 2024 EST
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned Jan 8, 2024 EST
Build Batch Data Pipelines on Google Cloud Earned Dec 20, 2023 EST
Build a Certification Study Guide: PDE Exam Prep Earned Dec 20, 2023 EST

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。

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完成 從 BigQuery 資料取得深入分析結果 技能徽章入門課程，即可證明您具備下列技能： 撰寫 SQL 查詢、查詢公開資料表、將樣本資料載入 BigQuery、使用 BigQuery 的查詢驗證工具 排解常見語法錯誤，以及在 Data Studio 中 透過連結 BigQuery 資料建立報表。

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完成 透過 BigQuery 建構資料倉儲 技能徽章中階課程，即可證明您具備下列技能： 彙整資料以建立新資料表、排解彙整作業問題、利用聯集附加資料、建立依日期分區的資料表， 以及在 BigQuery 使用 JSON、陣列和結構體。

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若想獲得技能徽章，請完成實現 Cloud Storage 和數據保護解決方案 技能徽章課程，您將在此瞭解如何建立 Cloud Storage bucket、 如何使用 Cloud Storage 指令列，以及如何在區塊中使用值區鎖定功能保護物件。

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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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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

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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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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data Engineer certification exam. You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.

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