|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/databricks-data-engineer-professional-practice-tests-in-2024/
课程评论：没有评论
课程名称：《Databricks 数据工程师专业实践测试 2025》 课程概述：本课程旨在为考生提供成为 Databricks 认证数据工程师所需的最新真实试题。该版本涵盖截至 2024 年 12 月 1 日的最新考试内容。通过本课程，您将自信地备考 Databricks 数据工程师专业认证考试！课程提供两个全面的实践测试，每个测试包含 60 道精心设计的问题，以及一个额外的奖学金测试，包含 25 道题目，确保涵盖所有考试主题。 课程特点： - **全面覆盖**：两个主测试各包含 60 道问题，设计与真实考试结构和难度相似。 - **额外实践测试**：第三个测试包含 25 道问题，为深化知识提供额外机会。 - **真实时间限制**：主测试每个120分钟，额外测试60分钟，模拟实际考试的时间约束。 涵盖主题： 1. **数据管理解决方案** - Lakehouse 架构：深入了解铜/银/金架构，包括表、视图和物理布局。 - 数据建模概念：学习约束、查找表和缓慢变化维度。 2. **数据处理管道** - 批处理 ETL 管道：构建和优化批处理 ETL 管道。 - 增量 ETL 管道：开发增量处理数据的管道。 - 数据去重：实施去重策略。 - 变更数据捕捉 (CDC)：有效传播变更。 - 工作负载优化：提高处理效率的技术。 3. **Databricks 平台和工具** - Databricks CLI：使用 CLI 部署基于笔记本的工作流。 - Databricks REST API：使用 REST API 配置和触发生产管道。 4. **生产管道最佳实践** - 安全与治理：使用 ACL 管理集群和作业权限，创建动态视图进行访问控制，确保符合 GDPR 和 CCPA 的安全数据删除。 5. **监控与日志记录** - 警报和存储配置：建立生产作业监控的警报和存储。 - 指标日志记录：记录和分析日志指标。 - 调试：学习在生产作业中调试错误的技巧。 6. **代码管理、测试和部署最佳实践**：掌握相对导入、作业调度和编排。 通过完成这些实践测试，您将充分准备好迎接 Databricks 数据工程师专业认证考试。祝您认证之路顺利！
This exam test is meticulously designed to equip you with the essential latest real questions required to become a certified Data Engineer Professional using Databricks.This version covers the currently live exam as of December 1, 2024.Prepare for the Databricks Data Engineer Professional certification exam with confidence! We provide two extensive practice tests, each with 60 carefully crafted questions, plus a bonus third practice test with 25 additional questions, ensuring comprehensive coverage of all exam topics.Key FeaturesComprehensive Coverage: Each of the two main practice tests includes 60 questions, designed to mimic the real exam structure and difficulty level.Bonus Practice Test: A third test with 25 questions provides an additional opportunity to refine your knowledge.Realistic Timing: Each main test is 120 minutes long, and the bonus test lasts 60 minutes, mirroring the time constraints of the actual exam.Topics CoveredData Management SolutionsLakehouse Architecture: Deep dive into the bronze/silver/gold architecture, including tables, views, and physical layout.Data Modeling Concepts: Learn about constraints, lookup tables, and slowly changing dimensions.Data Processing PipelinesBatch-Processed ETL Pipelines: Build and optimize batch ETL pipelines.Incremental ETL Pipelines: Develop pipelines that process data incrementally.Data Deduplication: Implement strategies for deduplicating data.Change Data Capture (CDC): Propagate changes effectively with CDC.Workload Optimization: Techniques to improve processing efficiency.Databricks Platform and ToolsDatabricks CLI: Deploy notebook-based workflows using the CLI.Databricks REST API: Configure and trigger production pipelines with the REST API.Production Pipeline Best PracticesSecurity and Governance: Manage cluster and job permissions using ACLs, create dynamic views for access control, and ensure secure data deletion in compliance with GDPR and CCPA.Monitoring and LoggingAlerting and Storage Configuration: Set up alerts and storage for production job monitoring.Metrics Logging: Record and analyze logged metrics.Debugging: Learn techniques for debugging errors in production jobs.Code Management, Testing, and DeploymentBest Practices: Master relative imports, job scheduling, and orchestration.By completing these practice exams, you will be fully prepared to tackle the Databricks Data Engineer Professional certification exam. Good luck on your journey to certification!
