Companies are increasingly turning to Amazon S3 as a storage layer for building data lakes, since on-premises solutions struggle with schema management, custom development, and operations burdens. Amazon S3 is a cost-effective option for storing an enormous quantity of disparate, complex data, but querying requires further work. Leveraging the natural fit of the MongoDB Query Language, MongoDB Atlas Data Lake intelligently distributes query execution to analyze Amazon S3 documents in place without the need to transfer data or define schema. With a live demonstration and market examples, learn how to build your data lake where your data already lives. This presentation is brought to you by MongoDB, an APN Partner.
