Rupesh Dandekar

Data engineering used to mean climbing from syntax up to intent. You wrote the code and hoped it expressed what you meant. Snowflake Snowflake CoCo inverts that stack. You start with intent, and the AI handles the implementation. In this 90-minute hands-on lab, working directly in Snowsight interface against live data, you will move from raw curiosity to a deployed Streamlit dashboard — just you, your data and an AI that already knows your schema. You will leave with three things: a working Streamlit app you built during the session, a prompt pattern library of five reusable templates for data engineering work and a mental model for intent-first development that you can apply on Monday morning.

Eaton Corporation is undergoing a significant transformation by migrating its data, analytics and AI capabilities to Snowflake, covering eight business functions/domains. This strategic move, guided by data mesh principles, aims to enhance decentralized data management, domain-oriented data ownership, and overall data accessibility. Concurrently, Eaton is implementing a finance transformation, utilizing a central finance alternative approach in Snowflake through a data products approach, to modernize financial operations and improve decision-making. Join this session to discover how these initiatives are driving efficiency, scalability and innovation across the organization.