🚀 Product Updates

Semantic Layer To-Dos New

When data analysts get a complex query request that isn’t answered by existing queries or Semantic Metrics/Models, they can edit or approve the AI-generated query so the business user gets an answer right away.

But if that question points to a recurring need for a structured data model, analysts can now flag it as a Semantic Layer To-Do.

These flagged requests sync directly into any VSCode-based environment via the runQL MCP (Model Context Protocol) Server, giving data analytics engineers a prioritized to-do list of models to create, complete with the full context and chat history behind each request.

Why it matters:

✅ Enables data teams to meet business user needs now and create semantic layer metrics/models for scale.
✅ Helps analytics engineers prioritize high-impact work based on business requests.
✅ Enables organizations to have confidence in data insights as they grow their library of trusted queries and semantic layer metrics/models for deterministic, trusted answers.

Enhanced Filtering & Pivot Tables for Business Users New

We’ve made column filters and pivot options more visible in data results, so business users can quickly filter, pivot, and explore data inside their chat thread in runQL, without exporting to Excel (but you can still export to Excel if you like!).

Why it matters:

✅ Empowers business users to work with data on their own
✅ Makes data exploration simpler and faster

Metadata Editing Workflows New

When a new data connection is added, data analysts are now automatically prompted to review and edit metadata, ensuring they see the generated semantic model and synthetic data right away.

Why it matters:

✅ Improves accuracy and documentation from the start
✅ Gives data teams better control over models and context

Fix SQL zip import Fix

Fix SQL zip import

We’re committed to helping your teams move faster, stay structured, and make confident, data-driven decisions, all within runQL.

— The runQL Team