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Juan Esteban Vallecilla Reyes

Member since 2022

Build a Certification Study Guide: PDE Exam Prep Earned Dec 7, 2023 EST
可靠的 Google Cloud 基礎架構：設計與程序 Earned Dec 7, 2023 EST
在 Google Cloud 為機器學習 API 準備資料 Earned Oct 30, 2023 EDT
Managing Security in Google Cloud Earned Oct 24, 2023 EDT
開始使用 Google Kubernetes Engine Earned Oct 23, 2023 EDT
Serverless Data Processing with Dataflow: Foundations Earned Jul 25, 2023 EDT
Logging and Monitoring in Google Cloud Earned Jul 25, 2023 EDT
在 Cloud Data Fusion 建構免程式碼管道 Earned Jun 26, 2023 EDT
Data Lake Modernization on Google Cloud: Cloud Data Fusion Earned May 9, 2023 EDT
DEPRECATED BigQuery for Data Warehousing Earned May 2, 2023 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned May 2, 2023 EDT
開始使用 Looker Earned Apr 19, 2023 EDT
Security Best Practices in Google Cloud Earned Apr 5, 2023 EDT
使用 Google Cloud 作業套件調度資源 Earned Mar 20, 2023 EDT
運用 Google Cloud 翻新基礎架構和應用程式 Earned Mar 19, 2023 EDT
運用 Google Cloud 探索資料轉換功能 Earned Mar 17, 2023 EDT
透過 Google Cloud 進行數位轉型 Earned Mar 14, 2023 EDT
透過 BigQuery 建構資料倉儲 Earned Sep 16, 2022 EDT
安全性與身分識別基礎知識 Earned Sep 13, 2022 EDT
[Deprecated] Cloud Logging Earned Sep 6, 2022 EDT
使用 BigQuery ML 為預測模型進行資料工程 Earned Sep 5, 2022 EDT
[DEPRECATED] Data Engineering Earned Aug 30, 2022 EDT
DEPRECATED BigQuery Basics for Data Analysts Earned Aug 24, 2022 EDT
Google Cloud 基礎知識：核心基礎架構 Earned Aug 24, 2022 EDT

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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這堂課程可讓參加人員瞭解如何使用確實有效的設計模式，在 Google Cloud 中打造相當可靠且效率卓越的解決方案。這堂課程接續了「設定 Google Compute Engine 架構」或「設定 Google Kubernetes Engine 架構」課程的內容，並假設參加人員曾實際運用上述任一課程涵蓋的技術。這堂課程結合了簡報、設計活動和實作研究室，可讓參加人員瞭解如何定義業務和技術需求，並在兩者之間取得平衡，設計出相當可靠、可用性高、安全又符合成本效益的 Google Cloud 部署項目。

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完成 在 Google Cloud 為機器學習 API 準備資料 技能徽章入門課程，即可證明您具備下列技能： 使用 Dataprep by Trifacta 清理資料、在 Dataflow 執行資料管道、在 Managed Service for Apache Spark 建立叢集和執行 Apache Spark 工作，以及呼叫機器學習 API，包含 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。

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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Identity, Resource Manager, Cloud IAM, Virtual Private Cloud firewalls, Cloud Load Balancing, Cloud Peering, Cloud Interconnect, and VPC Service Controls.

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歡迎參加「開始使用 Google Kubernetes Engine」課程。Kubernetes 是位於應用程式和硬體基礎架構之間的軟體層。如果您對這項技術感興趣，這堂課程可以滿足您的需求。有了 Google Kubernetes Engine，您就能在 Google Cloud 中以代管服務的形式使用 Kubernetes。 本課程的目標在於介紹 Google Kubernetes Engine (常簡稱為 GKE) 的基本概念，以及如何將應用程式容器化，以便在 Google Cloud 中執行。課程首先會初步介紹 Google Cloud，隨後簡介容器、Kubernetes、Kubernetes 架構和 Kubernetes 作業。

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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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Welcome to the two-part course on Logging, Monitoring, and Observability in Google Cloud. The core operations tools in Google Cloud break down into two major categories. The operations-focused components and the application performance management tools. This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring. After taking this course, it is suggested that you complete part 2, Observability in Google Cloud, to learn about the available application performance management tools.

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本課程提供 Cloud Data Fusion 的實作練習。這是一款雲端原生、 無程式碼的資料整合平台。ETL 開發人員、資料工程師和分析師 可運用預先建立的轉換和連接器， 輕鬆建構及部署管道，不必擔心編寫程式碼。本課程會以快速入門實驗室拉開序幕， 讓學員熟悉 Cloud Data Fusion UI，接著嘗試執行批次和即時管道， 以及使用內建 Wrangler 外掛程式， 對資料執行有趣的轉換。

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Welcome to Cloud Data Fusion, where we discuss how to use Cloud Data Fusion to build complex data pipelines.

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Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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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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完成「開始使用 Looker」技能徽章課程，即可獲得技能徽章， 您將從中瞭解如何使用 Looker Studio 和 Looker 分析、呈現及整理資料。

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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Storage access control technologies, Security Keys, Customer-Supplied Encryption Keys, API access controls, scoping, shielded VMs, encryption, and signed URLs. It also covers securing Kubernetes environments.

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各種規模的機構都開始運用雲端的強大功能和靈活性，徹底改變營運方式。不過，有效管理及擴充雲端資源可能是相當複雜的工作。本課程將探討在雲端中的現代營運、可靠性和韌性的基礎概念，以及 Google Cloud 如何協助您達成這些目標。本課程是 Cloud Digital Leader 學習路徑的一部分，旨在促進個人職能發展，並打造企業的未來。

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許多傳統企業使用舊版系統和應用程式，無法滿足現今客戶的期望。企業主管經常需要在維護老舊的 IT 系統，以及投資新產品/服務之間做出選擇。本課程將探討這些挑戰，並提供解決方案，說明如何運用雲端技術克服難題。 本課程是 Cloud Digital Leader 學習路徑的一部分，旨在促進個人職能發展，並打造企業的未來。

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雲端技術是強大的資產，與資料搭配後，將成為創新和提升客戶體驗的催化劑。「運用 Google Cloud 探索資料轉換功能」課程將探討機構如何運用雲端，讓資料更易於存取、做為行動依據和更有價值。 這門課程是 Cloud Digital Leader 學習路徑的一部分，旨在協助個人在職務上成長，並打造企業的未來。

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數位轉型是現代組織必經的關鍵旅程，而建立穩固的雲端運算基礎，是跨出有意義創新的第一步。本課程「透過 Google Cloud 進行數位轉型」，將會介紹核心技術和策略框架，協助組織革新營運方式，並探討基本的雲端概念、全球網路基礎架構和共同責任模式，幫助主管在雲端之路上自信前行。本課程是 Cloud Digital Leader 學習路徑的一部分，旨在促進個人職能發展，並打造企業的未來。

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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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Google Cloud 的服務在安全上絕不妥協， 因此開發了專用工具，確保所有專案安全無虞， 使用者也能妥善管理身分識別機制。在這堂入門課程中，您會實際使用 Google Cloud 的 Identity and Access Management (IAM) 服務， 練習管理使用者和虛擬機器帳戶。您將 佈建虛擬私有雲和 VPN 來熟悉網路安全功能，並瞭解有哪些工具 可防範資安威脅和資料遺失。

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Cloud Logging is a fully managed service that performs at scale. It can ingest application and system log data from thousands of VMs and, even better, analyze all that log data in real time. In this fundamental-level Quest, you learn how to store, search, analyze, monitor, and alert on log data and events from Google Cloud. The labs in the Quest give you hands-on practice using Cloud Logging to maximize your learning experience and provide insight on how you can use Cloud Logging to your own Google Cloud environment.

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完成使用 BigQuery ML 為預測模型進行資料工程技能徽章中階課程， 即可證明自己具備下列知識與技能：運用 Dataprep by Trifacta 建構連至 BigQuery 的資料轉換 pipeline； 使用 Cloud Storage、Dataflow 和 BigQuery 建構「擷取、轉換及載入」(ETL) 工作負載， 以及使用 BigQuery ML 建構機器學習模型。

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This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.

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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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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。

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