Which service should be used to transform data files before moving them to Azure Data Lake Storage?

Using Azure Data Factory to transform data files before moving them to Azure Data Lake Storage is the best choice due to its primary function as a data integration and transformation service within the Azure ecosystem. Azure Data Factory excels in orchestrating and automating data workflows, allowing users to create data pipelines that can ingest, prepare, and transform data from various sources.

This service supports various transformation activities, enabling users to apply complex data transformations and data manipulation. It can connect to a wide array of data sources, process the data using built-in or custom transformations, and effectively handle the orchestration of data movement. Once the necessary transformations are completed, Azure Data Factory can then seamlessly transfer the processed data files into Azure Data Lake Storage, ensuring that the data is in the right format and ready for analytics or further processing.

The other choices have their specific use cases but do not directly fit the need for transforming data files prior to storage in Data Lake Storage. For instance, Azure Databricks is more focused on providing a collaborative Apache Spark-based analytics platform, which, while capable of performing transformations, operates differently in the pipeline context compared to Azure Data Factory. Azure Storage Sync is primarily about syncing files between on-premises and Azure file shares, which does not involve transformation. Azure