With the massive influx in Generative AI applications, organisations are going through a critical phase of data infrastructure modernisation, laying the foundation for the future, and adapting to support growing data and AI needs. Many organisations that embraced cloud data warehouses (CDW) have ended up trying to use a data warehousing tool for ETL pipelines and data science purposes. These organisations likely have observed poor performance and limited capabilities due to the SQL-first implementation of these CDWs and limit their future analytical solutions.

Realising the limitation and pain with cloud data warehouses, organisations are turning to a Data Intelligence Platform architecture. 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. This session offers guidance on the migration methodology, technical approaches, automation tools, product/feature mapping, and best practices for migrating data, ELT pipelines and warehouses from CDW to Databricks.