How does a data factory differ from traditional ETL? A data factory is a modern approach to data integration and processing, typically implemented using cloud-based services. It offers a scalable and distributed architecture, allowing for efficient handling of large volumes of data. Data factories provide a workflow and orchestration framework to define complex data pipelines that automate tasks such as extraction, transformation, and loading. They leverage cloud-native features, such as managed services and connectors to various data sources, and offer monitoring and management capabilities. In contrast, traditional ETL is a batch processing approach focused on data transformation and often limited by hardware infrastructure. Data factories provide greater flexibility, scalability, and agility in managing data integration tasks.