中This comprehensive course empowers learners to construct, implement, monitor, and optimize data pipelines using Microsoft Azure Data Factory (ADF). Structured into four progressive modules, the course starts with foundational setup and connectivity, advancing to robust pipeline design, scheduling, debugging, and performance optimization using Azure Data Lake integration.
Microsoft Azure - Data Factory
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July 2025
作业
16 项作业
授课语言：英语（English）
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本课程是 Microsoft Azure: Cloud Solutions Mastery 专项课程 专项课程的一部分
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该课程共有4个模块
This module introduces learners to the foundational concepts of Azure Data Factory, including the interface, environment setup, and essential components such as copy operations, blob storage, and dataset creation. It prepares learners to begin working with ADF by configuring source and destination connections.
涵盖的内容
8个视频4个作业
This module guides learners through the process of building, debugging, and scheduling pipelines within Azure Data Factory. It explores copy activities, the authoring environment, and deploying pipelines using different scheduling strategies.
涵盖的内容
9个视频4个作业
This module focuses on monitoring pipeline execution, identifying failed runs, debugging issues, and interpreting pipeline behavior. It provides learners with skills to ensure the reliability and accuracy of data processing workflows.
涵盖的内容
9个视频4个作业
This module covers advanced integration techniques using Azure Data Lake, dynamic datasets, and pipeline parameterization. It emphasizes optimization, dataset configuration, and input validation for complex workflows.
涵盖的内容
8个视频4个作业
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