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During a data transformation process, you need to split a large dataset into smaller, more manageable subsets based on specific criteria. What techniques would you use to efficiently split the data while ensuring that the integrity and structure of the original dataset are preserved?
Explanation:
Using Azure Data Factory to automate the splitting process ensures efficiency and consistency in splitting large datasets into smaller subsets. This approach leverages the power of Azure's data integration service to handle the splitting based on predefined criteria, preserving the integrity and structure of the original dataset.