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所在平台: Udemy |
课程主页: https://www.udemy.com/course/aws-certified-data-engineer-associate-dea-c01-exam/
课程评论：没有评论
**AWS Certified Data Engineer - Associate (DEA-C01) 考试课程总结** 本课程旨在帮助学员通过 AWS Certified Data Engineer - Associate (DEA-C01) 考试。考试内容涵盖了数据工程师在 AWS 云环境中实施数据管道、处理成本和性能优化以及遵循最佳实践的能力。 **核心考试内容领域及权重:** * **数据摄取与转换 (34%)**: 涉及数据摄取、数据转换和数据管道编排，以及运用编程概念。 * **数据存储管理 (26%)**: 包括选择合适的数据存储、设计数据模型、数据模式目录化以及管理数据生命周期。 * **数据运营与支持 (22%)**: 涵盖数据管道的运维、维护和监控，以及数据分析和数据质量保障。 * **数据安全与治理 (18%)**: 涉及身份验证、授权、数据加密、隐私、数据治理，以及启用日志记录。 **推荐的通用 IT 知识:** * ETL 管道的设置和维护 * 高级编程概念 * Git 命令进行源代码管理 * 对数据湖的理解 * 网络、存储和计算基础知识 **AWS 相关知识要求:** * 运用 AWS 服务完成上述各项任务 * 理解 AWS 在加密、治理、保护和日志记录方面的服务 * 能够比较 AWS 服务的成本、性能和功能差异 * 在 AWS 服务上构建和执行 SQL 查询 * 使用 AWS 服务进行数据分析、质量和一致性检查 **考试范围之外的内容:** * 人工智能和机器学习任务 * 特定编程语言的语法知识演示 * 基于数据得出业务结论 **考试形式与评分:** * 考试包含单选题和多选题。 * 包含未计分的问题用于性能评估。 * 通过分数为 720 分，分数范围为 100-1,000 分。 * 采用补偿性评分模式，无需通过所有部分，各部分权重不同。
The DEA-C01 exam for AWS Certified Data Engineer - Associate assesses a candidate's proficiency in implementing data pipelines and addressing cost and performance concerns following best practices. The exam covers various tasks, including:Ingesting and transforming data, orchestrating data pipelines, and applying programming concepts.Selecting optimal data stores, designing data models, cataloging data schemas, and managing data lifecycles.Operationalizing, maintaining, and monitoring data pipelines, as well as analyzing data and ensuring data quality.Implementing authentication, authorization, data encryption, privacy, and governance, including enabling logging.Recommended general IT knowledge includes setting up and maintaining extract, transform, and load (ETL) pipelines, applying high-level programming concepts, using Git commands for source control, understanding data lakes, and having a grasp of networking, storage, and compute concepts.AWS-specific knowledge should cover using AWS services for the listed tasks, understanding AWS services for encryption, governance, protection, and logging, comparing AWS services for cost, performance, and functionality differences, structuring and running SQL queries on AWS services, and analyzing data for quality and consistency using AWS services.Tasks outside the scope of the exam include performing artificial intelligence and machine learning tasks, demonstrating programming language-specific syntax knowledge, and drawing business conclusions based on data.The exam comprises multiple-choice and multiple-response questions, with unscored questions included for performance evaluation. A passing score is 720, and results are reported on a scaled score of 100-1,000, reflecting overall performance. The exam uses a compensatory scoring model, meaning passing in each section is not required, and section weights vary.Content domains and weightings for the exam include:Data Ingestion and Transformation (34%)Data Store Management (26%)Data Operations and Support (22%)Data Security and Governance (18%)
