Manually document data lineage and metadata in the Databricks UI for each data asset, and create a shared documentation repository for data asset discoverability, relying on team members to update it regularly.

Utilize Databricks Delta Lake for storing and managing data, leveraging its built-in capabilities for automatic data lineage tracking and metadata management, and use Databricks notebooks for data exploration to enhance discoverability.

Develop a custom solution integrating Databricks notebooks with Apache Atlas for lineage tracking and a separate metadata repository, requiring significant development effort and maintenance.

Implement a third-party data catalog solution for lineage and metadata management, integrating it with Databricks for data processing, which may introduce additional licensing costs and integration complexity.