I need a Databricks SQL notebook that connects directly to our existing Delta Lake tables and produces an easy-to-explore summary-statistics report. The key to this job is interactivity: I want dropdown widgets at the top of the notebook (think product, region, date range, etc.) so non-technical users can slice the data without touching code. When any combination of those dropdowns is changed, the underlying SQL should refresh and rebuild the report on the fly. The final section of the notebook must return clear summary metrics—counts, sums, averages, minimums, maximums—and present them in a concise, readable format. If you can add lightweight visualisations using built-in Databricks display functions, even better, but the priority is the statistical table. Deliverables • A Databricks SQL notebook (.dbc or .html export) that: – pulls data only from Delta Lake tables I’ll specify, – defines and registers dropdown widgets for all dynamic filters, – runs parameterised SQL statements tied to those widgets, – outputs a refreshable summary statistics report, and – includes inline markdown explaining each step for future maintenance. Acceptance criteria • The notebook runs end-to-end in my workspace with one click of “Run All.” • Updating any dropdown re-executes the relevant cells and updates the report in under 10 seconds on our medium cluster. • No hard-coded paths or secrets—use Databricks utilities or widgets for configuration. If you have prior examples of interactive Delta Lake notebooks or tips for optimising Databricks SQL, feel free to mention them in your proposal. I’m ready to get started as soon as I see a clear plan and timeline.