Turn Your Data and ML Models in Snowflake into Interactive Applications with Python and Streamlit
Did you know that 73% of data is rendered effectively unused because it’s just too hard to build the tools to use it? That’s a whole lot of value (and consumption) left on the table! Streamlit’s open-source library makes it easy for data scientists and machine learning engineers to build interactive applications—all in Python—to explore better, surface, and operationalise data and models, simplifying to make it easy to collaborate with business teams.
With the integration of Streamlit, you’ll be able to build, deploy, and share your Streamlit app, all within Snowflake. This integration will be available towards the end of the year.
Join this live demo on 20 September, If you’d like to learn more about:
Snowpark for Python
How to build a Streamlit app and use Snowpark UDFs
Why Snowpark and Streamlit are the perfect match for Python developers and data scientists
How to increase your impact and bring your organisation together to collaborate, discover insights, and take action on data and ML models