Each step in Lakeflow Designer is represented as an operator, giving users a clear picture of how data changes throughout the workflow. This makes it easier to build, validate, and understand transformations as you go.

Lakeflow Designer extends the power of Databricks Lakeflow to a broader set of users, enabling no-code data preparation while still generating production-ready code under the hood. Workflows can be scheduled and operationalized through Lakeflow Jobs, making it easy to move from interactive data prep to production pipelines.

Self-service data prep is not a new idea, but existing tools sit outside your central data platform. That comes with tradeoffs:

1. Built natively on Databricks for governance and simplicity Lakeflow Designer runs directly where your data already lives - on Databricks. There’s no need to move data into a separate tool or onto your local machine. Data remains in place, governed by Unity Catalog from the start, while simplifying the overall data stack. Instead of managing a separate low-code tool with its own licensing, permissions, and administration model, organizations can enable self-service work directly within Databricks.