Datasets
When working with data in Azure Data Factory, datasets play a crucial role. They define the data structures or schema used in pipelines, essentially serving as a pointer to the data you want to move or transform. Datasets work in tandem with Linked Services to help ADF access, process, and manage data efficiently.
While Linked Services define where the data resides, datasets specify what part of the data to work with.
Why Are Datasets Important?
- Data interaction: datasets provide the schema and parameters that help ADF understand and interact with your data;
- Reusability: you can define datasets once and reuse them across multiple activities in pipelines;
- Flexibility: datasets allow dynamic configurations using parameters, enabling pipelines to handle variable data inputs or outputs.
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When working with data in Azure Data Factory, datasets play a crucial role. They define the data structures or schema used in pipelines, essentially serving as a pointer to the data you want to move or transform. Datasets work in tandem with Linked Services to help ADF access, process, and manage data efficiently.
While Linked Services define where the data resides, datasets specify what part of the data to work with.
Why Are Datasets Important?
- Data interaction: datasets provide the schema and parameters that help ADF understand and interact with your data;
- Reusability: you can define datasets once and reuse them across multiple activities in pipelines;
- Flexibility: datasets allow dynamic configurations using parameters, enabling pipelines to handle variable data inputs or outputs.
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