True or False: Data in Azure Data Lake can be historical or streamed from its source.

The statement is true. Azure Data Lake is designed to store vast amounts of data in its raw format, making it capable of handling both historical and streamed data from various sources.

Historical data can include information that has been collected over time, such as logs or records in structured files, while streamed data refers to data that is continuously generated and sent to the lake in real-time, such as telemetry data from sensors or logs from applications. This versatility allows Azure Data Lake to serve various analytics and data processing use cases, supporting batch processing of historical data and real-time processing of streamed data within the same system.

This functionality is one of the key benefits of using Azure Data Lake, enabling businesses to ingest, store, and analyze large volumes of diverse data.