The complex data environment today makes collaboration extremely difficult for data professionals, resulting in slow time to insight and leaving much value of data unrealized.
Snowpark, a developer framework of Snowflake, was built to solve this exact challenge by allowing different data professionals to bring their choice of language and collaborate in the same platform using the same data. Snowpark is designed to bring together data engineers, data scientists, and developers. It opens up data programmability so they can collaborate to better build and operationalize, while keeping their choice of languages, and benefit from the simplicity, access, performance, scalability, governance, and security of Snowflake’s Data Cloud.
Watch the Snowpark Day for a power-packed half-day event to learn:
- What Snowpark is and what you can build with it
- Example Snowpark use cases and customer stories
- How you can build with Snowpark using Java, Scala, and Python
- Latest innovations of Snowpark
- Benefits of Snowpark Accelerated: Snowpark’s powerful ecosystem program to bring more powerful integrations.
Snowpark & Snowpark Accelerated
Develop and operationalize your ML feature pipelines using Snowpark for Python UDFs and Apache Airflow
Discover Dataiku’s unique push down approach for agile and governed ML workflows
Transformer for Snowflake leverages Snowpark, making advanced transformations and data processing in Snowflake easy. Design and run simple to complex data transformations with an intuitive, visual UI.
Parsing HL7 Messages (Unstructured data) in Snowflake using Snowpark
Head of Partner Sales Engineering, Snowflake
Principal Data Platform Architect, Field CTO Office, Snowflake
Partner Solutions Engineer, StreamSets
Senior Product Marketing Manager(ML), Snowflake
Senior Product Marketing Manager, Snowflake
Senior Partner Sales Engineer, Snowflake
Partner Sales Engineer - AI & ML , Snowflake
Solutions Architect, Dataiku
Regional Technical Expert, NTT Data / Hashmap
Partner Senior Sales Engineer, Snowflake