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所在平台: Udemy |
课程主页: https://www.udemy.com/course/master-azure-databricks-for-data-engineers/
课程评论：没有评论
课程名称：Databricks - 精通 Azure Databricks 的数据工程师 课程概述： 本课程旨在帮助数据工程师利用 Azure 云平台掌握 Databricks 的使用。您将学习到以下内容： - 在 Azure 云中使用 Databricks - 使用 DBFS 和挂载存储 - 配置和使用 Unity Catalog - Unity Catalog 的用户管理与安全性 - 操作 Delta Lake 和 Delta 表 - 手动和自动的模式演变 - 向 Lakehouse 进行增量摄入 - 使用 Databricks Autoloader - Delta Live Tables 和 DLT 管道 - Databricks Repos 和工作流 - Databricks REST API 和 CLI - 期末项目 该课程还包含一个端到端的期末项目，旨在帮助学员理解实际项目的设计、编码、实施、测试及 CI/CD 方法。 适合人群： 本课程专为希望开发基于 Medallion 架构的 Lakehouse 项目的数据工程师设计。此外，也适合负责组织 Lakehouse 平台基础设施设计与构建的数据和解决方案架构师，以及那些虽不直接参与 Lakehouse 实施但与实施人员密切合作的管理者和架构师。 课程使用的 Spark 版本： 课程使用 Azure 云中的 Databricks 和 Apache Spark 3.5，所有示例代码和源代码均已在 Azure Databricks Cloud 上经过测试，使用 Databricks Runtime 13.3。
About the CourseI am creating Databricks - Master Azure Databricks for Data Engineers using the Azure cloud platform. This course will help you learn the following things.Databricks in Azure CloudWorking with DBFS and Mounting StorageUnity Catalog - Configuring and WorkingUnity Catalog User Provisioning and SecurityWorking with Delta Lake and Delta TablesManual and Automatic Schema EvolutionIncremental Ingestion into LakehouseDatabricks AutoloaderDelta Live Tables and DLT PipelinesDatabricks Repos and Databricks WorkflowDatabricks Rest API and CLICapstone ProjectThis course also includes an End-To-End Capstone project. The project will help you understand the real-life project design, coding, implementation, testing, and CI/CD approach. Who should take this Course?I designed this course for data engineers who are willing to develop Lakehouse projects following the Medallion architecture approach using the Databrick cloud platform. I am also creating this course for data and solution architects responsible for designing and building the organization's Lakehouse platform infrastructure. Another group of people is the managers and architects who do not directly work with Lakehouse implementation. Still, they work with those implementing Lakehouse at the ground level.Spark Version used in the Course.This course uses Databricks in Azure Cloud and Apache Spark 3.5. I have tested all the source codes and examples used in this course on Azure Databricks Cloud using Databricks Runtime 13.3.
