People change. Requirements change. Technology changes. Data changes.

Don't be afraid of change. Learn how to adapt and control the evolution of your data schemas in your Lakehouse so you can gracefully and harmoniously respond to changes of data from source systems, changes in requirements from your customers, and change how you want to present data, so that you can not worry.

In this session, we'll take a look at how to manage schema evolution when a source system changes the structure of the data it provides your Lakehouse using Databricks Autoloader, as well as how to control the evolution of your target analytical data model from physical schema, to semantic layer and what your customers see in their reports.