Elides Viloria
成为会员时间：2025
Serverless Data Processing with Dataflow: Foundations
Earned Jul 18, 2025 EDT
Build Streaming Data Pipelines on Google Cloud
Earned Jul 16, 2025 EDT
Build Batch Data Pipelines on Google Cloud
Earned Jul 10, 2025 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Jun 30, 2025 EDT
Google Cloud 数据工程简介
Earned Jun 17, 2025 EDT
在 Looker 中管理数据模型
Earned Jun 11, 2025 EDT
通过 BigQuery ML 创建机器学习模型
Earned Jun 9, 2025 EDT
从 BigQuery 数据中挖掘数据洞见
Earned Jun 4, 2025 EDT
Developing Data Models with LookML
Earned Jun 3, 2025 EDT
Analyzing and Visualizing Data in Looker
Earned May 28, 2025 EDT
为 Looker 信息中心和报告准备数据
Earned May 23, 2025 EDT
Google Cloud 数据分析基础知识
Earned May 8, 2025 EDT
Build a Certification Study Guide: PDE Exam Prep
Earned May 7, 2025 EDT
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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在本课程中，您将了解 Google Cloud 数据工程、数据工程师的角色和职责，以及相关的 Google Cloud 产品和服务。您还将了解如何应对数据工程挑战。
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完成中级技能徽章课程在 Looker 中管理数据 模型，展示以下方面的技能：维护 LookML 项目的健康状况；利用 SQL Runner 进行数据验证；采用 LookML 最佳实践；优化查询和 报告；以及实现永久性派生表和缓存政策。
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完成中级技能徽章课程通过 BigQuery ML 创建机器学习模型，展示您在以下方面的技能： 使用 BigQuery ML 创建和评估机器学习模型，以执行数据预测。
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完成入门级技能徽章课程“从 BigQuery 数据中挖掘数据洞见”，展示您在以下方面的技能： 编写 SQL 查询、查询公共表、将示例数据加载到 BigQuery 中、 在 BigQuery 中使用查询验证器排查常见的语法错误，以及通过连接到 BigQuery 数据在 Data Studio 中 创建报告。
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This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.
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In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
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完成为 Looker 信息中心和报告准备数据入门级技能徽章课程， 展现您在以下方面的技能：对数据进行过滤、排序和透视；将来自不同 Looker 探索的结果合并； 以及使用函数和运算符构建 Looker 信息中心和报告以用于数据分析和可视化。
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了解如何在 Google Cloud 上将原始数字转化为清晰、以数据为依据的决策。通过实操实验和实际应用场景，本新手级课程将引导您在 BigQuery 中查询数据、在 Looker 中探索趋势，以及在数据洞察中制作可共享的交互式报告。
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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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