Databricks is a leading data and AI platform used by enterprise data engineers, analysts, data scientists, and platform admins. One of its key surfaces, Databricks SQL, serves both technical and semi-technical users who need fast, reliable analytics workflows across queries, dashboards, and collaboration.
The UX team has been asked to improve the Databricks SQL query and dashboarding experience because adoption is growing, but user feedback is inconsistent. Product analytics show that weekly active users in Databricks SQL have grown 22% year over year, yet only 38% of new workspace users who open the SQL Editor create a second query within 14 days. Support tickets and research notes suggest multiple possible issues: query setup confusion, poor discoverability of saved queries, dashboard trust concerns, and friction switching between SQL Editor, queries, and dashboards.
Leadership wants a clear definition of the core user problem before committing design and engineering resources. You are the PM partner to a UX/UI designer and need to explain how you would use data and research to frame the problem correctly rather than jumping to solutions.