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所在平台: Udemy |
课程主页: https://www.udemy.com/course/azure-data-engineering-with-adf-adb-synapse-and-powerbi/
课程评论：没有评论
**课程名称：** Azure 数据工程：ADF、ADB、Synapse 与 Power BI **课程概述：** 本课程旨在教授学员如何利用 Microsoft Azure 服务构建一个统一的数据平台，以高效地收集、处理、分析和可视化数据，从而支持企业做出明智的决策。课程将重点介绍 Azure Data Factory (ADF)、Azure Synapse Analytics (原 SQL Data Warehouse)、Azure Databricks 和 Power BI 的集成应用。 **项目目标：** * **数据摄取与集成 (ADF):** 使用 Azure Data Factory 编排从各种数据源（数据库、文件、流式数据源）的数据摄取，并实现数据清理、转换和加载到集中式数据湖或数据仓库。 * **可扩展的数据仓库 (Synapse Analytics):** 部署 Azure Synapse Analytics 创建可扩展、高性能的数据仓库解决方案，设计和优化数据模型以支持复杂的分析查询和报告。 * **高级分析与数据处理 (Azure Databricks):** 利用 Azure Databricks 对海量数据进行高级分析、机器学习和数据处理。开发基于 Spark 的 ETL 流程，构建预测模型，并使用 Python 或 Scala 进行数据探索和可视化。 * **实时分析与流处理:** 使用 Azure Stream Analytics 或 Azure Databricks 流处理能力实现实时数据处理和分析。分析来自 IoT 设备、传感器或社交媒体平台的流数据，实时获取洞察并检测模式。 * **商业智能与报告 (Power BI):** 使用 Power BI 开发交互式仪表板和报告，可视化从统一数据平台获得的洞察。创建丰富的可视化、下钻报告和高管仪表板，赋能量化业务用户。 **项目交付成果：** * 用于数据摄取、转换和加载的 Azure Data Factory 管道。 * 经过优化的数据模型的 Azure Synapse Analytics 数据仓库。 * 用于高级分析、ETL 和机器学习的 Azure Databricks Notebook。 * 使用 Azure Stream Analytics 或 Azure Databricks 流处理的实时分析解决方案。 * 用于商业智能和决策支持的 Power BI 仪表板和报告。 **项目优势：** * 简化数据集成和处理工作流。 * 提高数据准确性、一致性和可靠性。 * 增强分析工作负载的可扩展性和性能。 * 为主动决策提供实时洞察。 * 通过自助式分析和报告能力赋能量化业务用户。 **结论：** 本课程旨在展示 Microsoft Azure 服务在构建现代数据平台方面的强大功能，该平台能够整合来自不同来源的数据，执行高级分析，并提供可操作的洞察以推动业务成功。 **数据集：** [https://g-ithu-b-.c-om/sanish21/ThomTechPOC](https://g-ithu-b-.c-om/sanish21/ThomTechPOC)
Project Description:In today's data-driven world, organizations need robust platforms to efficiently collect, process, analyze, and visualize data to drive informed decision-making. This project aims to design and implement a unified data platform leveraging Microsoft Azure services including Azure Data Factory (ADF), Azure Synapse Analytics, Azure Databricks, and Power BI.Project Goals:Data Ingestion and Integration: Utilize Azure Data Factory to orchestrate the ingestion of data from various sources including databases, files, and streaming sources. Implement data integration pipelines to cleanse, transform, and load data into a centralized data lake or data warehouse.Scalable Data Warehousing: Deploy Azure Synapse Analytics (formerly SQL Data Warehouse) to create a scalable and performant data warehouse solution. Design and optimize data models to support complex analytical queries and reporting requirements.Advanced Analytics and Data Processing: Leverage Azure Databricks to perform advanced analytics, machine learning, and data processing tasks on large volumes of data. Develop Spark-based ETL processes, build predictive models, and perform data exploration and visualization using Python or Scala.Real-time Analytics and Streaming: Implement real-time data processing and analytics using Azure Stream Analytics or Azure Databricks streaming capabilities. Analyze streaming data from IoT devices, sensors, or social media platforms to gain insights and detect patterns in real-time.Business Intelligence and Reporting: Develop interactive dashboards and reports using Power BI to visualize insights derived from the unified data platform. Create rich visualizations, drill-down reports, and executive dashboards to empower business users with actionable insights.Project Deliverables:Azure Data Factory pipelines for data ingestion, transformation, and loading.Azure Synapse Analytics data warehouse with optimized data models.Azure Databricks notebooks for advanced analytics, ETL, and machine learning.Real-time analytics solutions using Azure Stream Analytics or Azure Databricks streaming.Power BI dashboards and reports for business intelligence and decision support.Project Benefits:Streamlined data integration and processing workflows.Improved data accuracy, consistency, and reliability.Enhanced scalability and performance for analytics workloads.Real-time insights for proactive decision-making.Empowered business users with self-service analytics and reporting capabilities.Conclusion:This project aims to demonstrate the capabilities of Microsoft Azure services for building a modern data platform that integrates data from disparate sources, performs advanced analytics, and delivers actionable insights to drive business success.Data Sets:"https://g-ithu-b-.c-om/sanish21/ThomTechPOC"
