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所在平台: Udemy |
课程主页: https://www.udemy.com/course/end-to-end-azure-data-engineering-real-time-project/
课程评论：没有评论
课程名称：端到端Azure数据工程实时项目 - 3小时 概述：本课程将带您构建一个完整的端到端Azure数据工程项目。我们将从数据摄取、数据转换、数据加载到报告，创建一个完整的数据平台。本项目所涉及的工具包括：Azure Data Factory、Azure Data Lake Storage Gen2、Azure Databricks、Azure Synapse Analytics、Azure Key Vault、Microsoft Entra ID（前称AAD）及Microsoft Power BI。 项目用例是通过Azure Data Factory从本地SQL Server数据库摄取数据表，然后将数据存储在Azure Data Lake中。接着，使用Azure Databricks将原始数据转换成最干净的数据格式，随后通过Azure Synapse Analytics加载清洗后的数据，最后借助Microsoft Power BI集成Azure Synapse Analytics，构建一个互动式仪表板。此外，我们还会使用Microsoft Entra ID（前称AAD）和Azure Key Vault进行监控和治理。 在该视频中，我还涵盖了完整的端到端管道测试，从新的数据摄取开始，经过数据转换，直到更新使用Power BI创建的报告。
In this course, let's build a complete End to End Azure Data Engineering Project. In this project we are going to create an end to end data platform right from Data Ingestion, Data Transformation, Data Loading and Reporting. The tools that are covered in this project are,Azure Data Factory Azure Data Lake Storage Gen2Azure Databricks Azure Synapse Analytics Azure Key vault Microsoft Entra ID (Previously called as AAD) andMicrosoft Power BI The use case for this project is building an end to end solution by ingesting the tables from on-premise SQL Server database using Azure Data Factory and then store the data in Azure Data Lake. Then Azure databricks is used to transform the RAW data to the most cleanest form of data and then we are using Azure Synapse Analytics to load the clean data and finally using Microsoft Power BI to integrate with Azure synapse analytics to build an interactive dashboard. Also, we are using Microsoft Entra ID ( Previously called as AAD) and Azure Key Vault for the monitoring and governance purpose. In this video, I have also covered the complete end to end pipeline testing right from how a new data gets ingested followed by the data transformation until it goes updating the report that we will be creating using the Power BI
