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所在平台: Udemy |
课程主页: https://www.udemy.com/course/dp-203-azure-data-engineer-associate-training/
课程评论：没有评论
**微软 Azure 数据工程课程总结** 本课程专注于在微软 Azure 云平台上实现和管理数据工程工作负载。学员将学习如何利用 Azure Synapse Analytics、Azure Data Lake Storage Gen2、Azure Stream Analytics、Azure Databricks 等关键 Azure 服务，完成常见的数据工程任务。 **核心学习内容包括：** * **数据管道编排：** orchestrating data transfer and transformation pipelines * **数据湖操作：** working with data files in a data lake * **数据仓库构建：** creating and loading relational data warehouses * **实时数据处理：** capturing and aggregating streams of real-time data * **数据资产管理：** tracking data assets and lineage 通过本课程的学习，您将获得在 Azure 上构建分析解决方案所需的数据工程知识和实践技能，为成为数据专业人士、数据架构师或商业智能专业人士奠定基础。本课程将为您提供 Azure 端到端大数据处理的全面视角。 **技能要求：** 课程面向具备以下经验的学习者： * 在整合、转换来自结构化、非结构化和流式数据系统的数据方面拥有专业知识。 * 能够将数据整合为适合分析解决方案的模式。 **Azure 数据工程师的角色：** 作为 Azure 数据工程师，您将协助利益相关者通过数据探索理解数据，并利用多种工具和技术构建和维护安全合规的数据处理管道。您将运用各种 Azure 数据服务和框架来存储和生产经过清洗和增强的数据集，以支持分析工作。
In this course, you will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage. You can become a data professional, a data architect, or a business intelligence professional by learning about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. This course will give you a flavor of end-to-end processing of big data in Azure.As a candidate for this certification, you should have subject matter expertise in integrating, transforming, and consolidating data from various structured, unstructured, and streaming data systems into a suitable schema for building analytics solutions.As an Azure data engineer, you help stakeholders understand the data through exploration, and build and maintain secure and compliant data processing pipelines by using different tools and techniques. You use various Azure data services and frameworks to store and produce cleansed and enhanced datasets for analysis.
