Five keys to integrating Snowflake and Databricks into your business

Inside the report

Data teams now run customer engagement, financial operations and AI workflows from Snowflake and Databricks, in real time. Getting that data back into the business takes a different kind of integration, one built for reverse ETL.

This guide outlines five key principles to help you operationalize your data warehouses and build AI-ready, scalable workflows across the business.

What you’ll learn

• How to unify your stack: Consolidate ETL, reverse ETL, API management, and AI into one platform to eliminate fragmented architectures.
• How to make Snowflake and Databricks data AI-ready and accessible: Structure and sync warehouse data in real time, connect it to LLMs where needed, and give teams tools to act on it—without waiting on engineering.
• How to build responsibly at scale: Leverage serverless infrastructure for dynamic workloads while ensuring trust with strong governance, tokenization, and audit trails.

Go deeper

For the full customer 360, from matching records to putting health back in the CRM, with a how-to guide for each stage, see customer 360, end to end.