Data Exploration Skill

To build ad-hoc data visualizations, use the Explore Data Canvas workflow to drag cubes or tables onto a canvas, select desired fields, choose chart types, and refine outputs visually before publishing the result as a live dashboard.

Yes, you can generate custom SQL or Groovy scripts from plain-English prompts using Chat2DB AI assistance, which drafts queries using schema metadata and semantic-layer definitions without accessing or exfiltrating underlying row-level data.

A semantic layer provides pre-defined business dimensions, measures, and joins that keep metrics consistent across BI dashboards, reducing complexity and ensuring accurate data exploration without needing to manually define calculations each time.

To add advanced logic like window functions or custom bucketing, switch from the visual builder to Finetune mode, which allows you to directly edit or generate SQL and Groovy scripts to apply complex mathematical operations and custom limits.

Yes, it supports selecting pre-configured database connections including the Northwind Sample connection, allowing you to immediately drop semantic-layer cubes, select measures and dimensions, and iterate on visual outputs without manual setup.

AI-assisted SQL generation is limited to using schema metadata for drafting queries and does not access or exfiltrate actual data rows, meaning generated scripts must be executed within the Explore Data Canvas environment to validate against live data.