Next steps

Provides different options to get ideas about how to build on top of the ADLS ingest flow management use case.

You have built a simple data flow for an easy way to move data to Azure Data Lake Storage. This example data flow enables you to easily design more complex data flows for moving and processing data as part of cloud migration efforts.

Moving data to the cloud is one of the cornerstones of any cloud migration. Cloud environments offer numerous deployment options and services.

You can build a combination of on-premise and public cloud data storage. You can use this solution as a path to migrate your entire data to the cloud over time—eventually transitioning to a fully cloud-native solution or to extend your existing on-premise storage infrastructure, for example for a disaster recovery scenario. Cloud storage can provide secure, durable, and extremely low-cost options for data archiving and long-term backup for on-premise datasets.

You can also use cloud services without storing your data in the cloud. In this case you would continue to use your legacy on-premise data storage infrastructure, and work with on-demand, cloud-based services for data transformation, processing and analytics with the best performance, reliability and cost efficiency for your needs. This way you can manage demand peaks, provide higher processing power, and sophisticated tools without the need to permanently invest in computer hardware.