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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practice-databricks-certified-data-engineer-professional/
课程评论：没有评论
Coursera 上的“Practice: Databricks Certified Data Engineer Professional”课程旨在帮助学员为 Databricks 认证数据工程师专业级别考试做好准备。 **课程概述：** 该认证考试旨在评估个人使用 Databricks 平台执行高级数据工程任务的能力。课程内容涵盖了对 Databricks 平台及其开发者工具的深入理解，包括 Apache Spark™、Delta Lake、MLflow、Databricks CLI 和 REST API。重点在于学习如何构建优化且经过清洗的 ETL（提取、转换、加载）管道。此外，课程还将教授如何运用通用的数据建模概念将数据建模到 Lakehouse 中。最后，课程也会涉及如何确保数据管道在部署前是安全、可靠、有监控和经过测试的。通过此考试的学员将能胜任使用 Databricks 及其相关工具完成高级数据工程任务。 **考试详情：** * **类型：** 监考认证考试 * **问题数量：** 60 道 * **时间限制：** 120 分钟 * **注册费用：** 200 美元 * **问题类型：** 多项选择题 * **考试辅助：** 不允许使用任何辅助工具 * **语言：** 英语、日语、巴西葡萄牙语、韩语 * **交付方式：** 在线监考 * **先决条件：** 无，但强烈推荐相关培训 * **推荐经验：** 至少 1 年以上执行考试指南中所述数据工程任务的实践经验 * **有效期：** 2 年 * **重认证：** 每两年需要重认证以保持认证状态。重认证必须参加当前版本的考试。 **考试内容构成：** * Databricks 工具：20% * 数据处理：30% * 数据建模：20% * 安全与治理：10% * 监控与日志记录：10% * 测试与部署：10%
Databricks Certified Data Engineer ProfessionalThe Databricks Certified Data Engineer Professional certification exam assesses an individual's ability to use Databricks to perform advanced data engineering tasks. This includes an understanding of the Databricks platform and developer tools like Apache Spark™, Delta Lake, MLflow, and the Databricks CLI and REST API. It also assesses the ability to build optimized and cleaned ETL pipelines. Additionally, the ability to model data into a lakehouse using knowledge of general data modeling concepts will be assessed. Finally, being able to ensure that data pipelines are secure, reliable, monitored and tested before deployment will also be included in this exam. Individuals who pass this certification exam can be expected to complete advanced data engineering tasks using Databricks and its associated tools.Assessment DetailsType: Proctored certificationTotal number of questions: 60Time limit: 120 minutesRegistration fee: $200Question types: Multiple choiceTest aides: None allowedLanguages: English, 日本語, Português BR, 한국어Delivery method: Online proctoredPrerequisites: None, but related training highly recommendedRecommended experience: 1+ years of hands-on experience performing the data engineering tasks outlined in the exam guideValidity period: 2 yearsRecertification: Recertification is required every two years to maintain your certified status. To recertify, you must take the current version of the exam. Please review the "Getting Ready for the Exam" section below to prepare for your recertification exam.Unscored content: Exams may include unscored items to gather statistical information for future use. These items are not identified on the form and do not impact your score. Additional time is factored into the exams to account for this content.The exam covers:Databricks Tooling - 20%Data Processing - 30%Data Modeling - 20%Security and Governance - 10%Monitoring and Logging - 10%Testing and Deployment - 10%
