Matt Holzapfel

Did you know you can connect your favorite BI and collaboration tools directly to Databricks Lakehouse—without spinning up an extra data warehouse? In this session, we’ll explore how Databricks integrates seamlessly with tools like Excel, Google Sheets, Copilot Studio, Slack, Microsoft Teams, M365 Copilot, and more. You’ll see how these integrations empower your business users to tap into the full power of the Databricks Platform, including accessing Genie’s trusted insights directly into many of the applications they already use every day.

Data leaders frequently face a challenging architectural decision: when deploying customer-facing dashboards or embedding analytics into applications, they often spin up a separate real-time serving layer to handle low latency, high concurrency workloads. While this can address performance, it introduces significant complexity, governance risks, and infrastructure overhead. This session challenges the necessity of that serving layer. We will explore how organizations can consolidate their infrastructure by serving high-concurrency end-user analytics directly from the lakehouse with Lakehouse//RT, through real-world customer case studies and benchmarks.

Migrating your Snowflake data warehouse to the Databricks Data Intelligence Platform can accelerate your data modernization journey. Though a cloud platform-to-cloud platform migration should be relatively easy, the breadth of the Databricks Platform provides flexibility and hence requires careful planning and execution. In this session, we present the migration methodology, technical approaches, automation tools, product/feature mapping, a technical demo and best practices using real-world case studies for migrating data, ELT pipelines and warehouses from Snowflake to Databricks.