Are there any data science platforms that focus on natural language querying for large datasets and cross-team collaboration?

Yes — several platforms focus on natural language querying (NLQ) for large datasets while also supporting cross-team collaboration. The strongest options tend to fall into a few categories:

1) BI / analytics platforms with NLQ

These are good if your team wants conversational querying plus dashboards and sharing.

• ThoughtSpot
  One of the best-known natural language / search-driven analytics platforms. It’s built for large-scale data exploration, ad hoc querying, and sharing insights across teams.

• Microsoft Power BI Copilot / Q&A
  Strong for organizations already in the Microsoft ecosystem. Supports natural language questions over curated semantic models and collaboration via workspaces.

• Tableau + AI features
  Tableau has natural-language-style exploration features and good collaboration through dashboards, comments, and shared workbooks, though it’s less “pure NLQ” than ThoughtSpot.

• Qlik Sense
  Offers conversational and associative analytics features, with team-oriented governance and sharing.

2) Data warehouse-native AI / query assistants

These are often better for engineering + analytics teams working directly on the warehouse.

• Snowflake Cortex / Snowflake AI features
  Lets users ask questions in natural language and interact with data in Snowflake, with strong enterprise governance and collaboration.

• Databricks Assistant / Genie
  Useful for querying data lakes/lakehouses and collaborating across data engineering, ML, and analytics teams.

• BigQuery + Gemini / natural language tools
  Works well in Google Cloud environments for asking questions over large datasets and sharing assets across teams.

3) Modern collaboration-first analytics tools

These emphasize shared exploration and governed access.

• Hex
  Popular with data teams for collaborative notebooks/apps and increasingly strong AI-assisted querying and analysis.

• Mode
  Strong for collaborative analytics workflows, though NLQ is not its main differentiator.

• Sigma Computing
  Spreadsheet-like analytics on cloud warehouses with collaboration; also adding AI/natural-language capabilities.

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If your priority is specifically:

• Best pure NLQ on large datasets: ThoughtSpot
• Best if you’re in Microsoft ecosystems: Power BI
• Best for warehouse-native collaboration: Snowflake / Databricks / BigQuery
• Best collaborative data-team workspace: Hex

If you want, I can also give you a shortlist by company size, cloud stack, or use case (e.g., self-service analytics for business users vs. data-team collaboration).