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所在平台: Udemy |
课程主页: https://www.udemy.com/course/google-dataform-interview-guide-6-practice-exams/
课程评论：没有评论
课程名称：谷歌 Dataform 面试指南：六套练习考试 课程概述： 您在为与 Dataform 相关的面试做准备，还是希望巩固数据转换和管道编排的知识？本课程是您掌握 Dataform 的终极指南。Dataform 是一个协作平台，能够在现代云数据仓库（如 BigQuery、Snowflake 和 Redshift）中简化基于 SQL 的数据工作流。该课程提供六套精心策划的练习测验，旨在加强您对核心概念、技术配置和 Dataform 在分析工程中的实际应用的理解。 主要内容： 1. Dataform 介绍：了解 Dataform 的定义及其如何简化现代云环境中的 SQL 工作流编排和数据转换。 2. Dataform 架构：深入了解核心组件，包括 Dataform CLI、Web 平台和支持转换逻辑及执行流程的元数据层。 3. 设置 Dataform：学习如何安装 Dataform CLI，初始化项目，并与云数据仓库（如 BigQuery、Snowflake 和 Redshift）连接。 4. 使用 SQL 进行数据建模：探索如何编写模块化和参数化的 SQL 脚本，管理数据依赖关系，定义动态数据转换。 5. 依赖管理：掌握 ref() 等技术，定义上下游关系，可视化 DAG，处理循环依赖以实现高效数据流。 6. 工作流编排：学习通过 Dataform Web 或 CLI 进行 SQL 工作流的调度、执行和监控，同时为大数据集配置增量处理。 7. 测试和验证：了解如何实施断言和数据质量检查，集成 CI/CD 管道，并通过自动化测试防止错误。 8. 协作与版本控制：通过使用基于 Git 的版本控制与团队协作，跟踪更改、管理拉取请求和解决冲突。 9. 监控与日志记录：学习如何监控管道运行、调试错误、设置警报，以及跟踪执行指标以维护工作流健康。 10. 与数据生态系统的集成：探索与数据仓库、BI 工具（如 Looker、Power BI）及像 Airflow 或 Prefect 等编排系统的原生集成。 11. 性能优化：使用优化 SQL、分区/聚集表和增量处理来设计高效工作流，以提高速度和减少成本。 12. 现实世界应用及案例研究：接触常见行业用例，包括 ETL/ELT 管道设计、业务报告自动化和协作数据操作。 本课程提供450多个经过精心设计的问题，保证您能够为真实世界的面试、评估和 Dataform 的实际应用做好充分准备。
Are you preparing for a Dataform-related interview or looking to solidify your knowledge in data transformation and pipeline orchestration? This course is your ultimate guide to mastering Dataform - a collaborative platform that enables streamlined SQL-based data workflows in modern cloud data warehouses like BigQuery, Snowflake, and Redshift.This course offers 6 curated practice tests, each designed to reinforce your understanding across core concepts, technical configurations, and real-world implementation of Dataform in analytics engineering.Key Topics Covered:1. Introduction to DataformUnderstand what Dataform is and how it simplifies SQL workflow orchestration and data transformations across modern cloud environments.2. Architecture of DataformGet deep insights into the core components including the Dataform CLI, Web platform, and the metadata layer that powers transformation logic and execution flows.3. Setting Up DataformLearn how to install the Dataform CLI, initialize projects, and connect with cloud data warehouses such as BigQuery, Snowflake, and Redshift.4. Data Modeling with SQLExplore how to write modular and parameterized SQL scripts, manage data dependencies, and define dynamic data transformations.5. Dependency ManagementMaster techniques like ref() to define upstream/downstream relationships, visualize DAGs, and handle circular dependencies for efficient data flows.6. Workflow OrchestrationLearn to schedule, execute, and monitor SQL workflows through Dataform Web or CLI, while configuring incremental processing for large datasets.7. Testing and ValidationUnderstand how to implement assertions and data quality checks, integrate CI/CD pipelines, and prevent errors through automated testing.8. Collaboration and Version ControlWork collaboratively with your team by using Git-based version control, tracking changes, managing pull requests, and resolving conflicts.9. Monitoring and LoggingLearn how to monitor pipeline runs, debug errors, set alerts, and track execution metrics for ongoing workflow health.10. Integration with Data EcosystemExplore native integrations with warehouses, BI tools (e.g., Looker, Power BI), and orchestration systems like Airflow or Prefect.11. Performance OptimizationDesign efficient workflows using optimized SQL, partitioned/clustering tables, and incremental processing to improve speed and reduce cost.12. Real-World Applications and Use CasesGain exposure to common industry use cases including ETL/ELT pipeline design, business reporting automation, and collaborative data operations.With 450+ carefully crafted questions, this course ensures you have hands-on preparation for real-world interviews, assessments, and practical implementations in Dataform.
