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所在平台: Udemy |
课程主页: https://www.udemy.com/course/databricks-certified-data-engineer-associate-exams-2025/
课程评论：没有评论
**Coursera 课程总结：Databricks 认证数据工程师助理考试 2025** 本课程旨在帮助学习者为 Databricks 认证数据工程师助理 2025 年考试做好准备。课程内容聚焦于 Databricks Lakehouse 平台、使用 Spark SQL 和 Python 进行 ELT、增量数据处理、生产流水线以及数据治理。 **考试详情：** * **考试类型：** 监考认证考试 * **问题数量：** 考试时会遇到 50 道题，最终成绩基于 45 道题，其中部分新题目可能需要选择 2 个正确答案（共 5 个选项）。 * **时间限制：** 90 分钟 * **注册费用：** 200 美元 * **题目类型：** 单选（每题 4 个选项） * **考试辅助：** 不允许使用任何考试辅助工具 * **语言：** 英语、日语、巴西葡萄牙语、韩语 * **考试方式：** 在线监考 * **先决条件：** 无，但强烈推荐相关培训 * **推荐经验：** 具备至少 6 个月的数据工程实践经验，涵盖考试大纲中的相关任务 * **有效期：** 2 年 **考试内容分布（高层主题）：** * Databricks Lakehouse 平台：24% * 使用 Spark SQL 和 Python 进行 ELT：29% * 增量数据处理：22% * 生产流水线：16% * 数据治理：9% 本课程提供高质量、最新且精心筛选的考试题目及详细解释，帮助学习者高效备考。祝您考试顺利！
Databricks frequently updates their products, which means the content and question bank for their certification exams are also continuously evolving. I aim to provide an updated set of exam questions with high quality, including the latest and carefully curated ones, along with detailed explanations. This exam will help learners prepare more effectively for the 2025 Data Engineer Associate certification exam.About the exam:Type: Proctored certificationTotal number of questions: 45Time limit: 90 minutesRegistration fee: $200Question types: Multiple choice (4 options for each question)Test aides: None allowedLanguages: English, 日本語, Português BR, 한국어Delivery method: Online proctoredPrerequisites: None, but related training highly recommendedRecommended experience: 6+ months of hands-on experience performing the data engineering tasks outlined in the exam guideValidity period: 2 yearsPS: you may encounter 50 questions in the real exam since sometimes Databricks evaluate the difficulty of new questions before releasing them. Your final score will be based on only 45 questions. For these new questions, you may also need to select 2 answers from the given 5 options.The questions will be distributed by high-level topic in the following way:Databricks Lakehouse Platform - 24% (11/45)ELT with Spark SQL and Python - 29% (13/45)Incremental Data Processing - 22% (10/45)Production Pipelines - 16% (7/45)Data Governance - 9% (4/45)Good luck and enjoy!
