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 using their preferred languages, and benefit from the simplicity, access, performance, scalability, governance, and security of Snowflake’s Data Cloud.
Join 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
- The latest about Snowpark for Python capabilities and other improvements
- Benefits of Snowpark Accelerated: Snowpark’s powerful ecosystem program to bring more powerful integrations
- Featuring partner and customer stories using Snowpark for Python
- Use Snowpark using SageMaker Studio Lab, Amazon’s free hosted notebook environment
Speakers
Julian Forero
Senior Product Marketing Manager at Snowflake
Shiyi Gu
Senior Product Marketing Manager at Snowflake
Tom Manfredi
Senior Partner Sales Engineer at Snowflake
Mehul Patel
Senior, Financial Services consulting at EY Comply
Vishal HP
Senior, Financial Services consulting at EY Comply
Michael Krause
Managing Director, Chief Technology Officer at EY Comply
Durgesh Sakhardande
Manager, Financial Services consulting at EY Comply
Matt Bleifer
Group Product Manager at Tecton
Caleb Baechtold
Data Platform Architect, Field CTO Office at Snowflake
Agenda
Snowflake
Snowpark & Snowpark Accelerated
Snowflake
Develop and operationalize your ML feature pipelines using Snowpark for Python UDFs and Apache Airflow