the data warehouse for data lake analytics
To maximize the utility of a data lake, you need to create real-time dashboards to report on the data, run fast analytics to uncover insights and relationships, interactively explore the data to find new trends, and much more. Plus, you want to accomplish all this across the multiple workgroups and stakeholders that need concurrent access to the data.
Executing these broad set of use cases requires more capabilities than the typical legacy on-premises data lake. For 2019 and beyond, you need to look toward the cloud. And, you need a highly performant data warehouse, along with your data lake in the cloud. But not just any data warehouse. Snowflake, the only data warehouse built for the cloud, provides a robust solution capable of low-latency relational analytics, self-service data access and queries, along with virtually unlimited multi-workgroup concurrency scaling.
With Snowflake, you have the power and flexibility of two worlds. For maximum functionality, the highest performance, and the deepest relational insights, land data such as JSON, Parquet, CSV and ORC directly into Snowflake and maintain it all within a single, integrated environment. No ETL effort, pre-transformations or pre-schemas required. Or, land your data in an S3 or ADLS data lake and directly query with Snowflake.