Smart Query – Natural language to SQL

Smart Query: Turn Natural Language into SQL

See how prompts translate into safe, schema-aware SQL with an editable query box, results preview, and export options.

• 7-minute read

Taptic Data Smart Query converts plain-English prompts into clean, schema-aware SQL you can edit and run instantly. It’s designed for teams that want fast analysis without memorizing table names or writing every query from scratch.

How Smart Query Works

  1. Type a prompt in the AI input (e.g., “Total revenue by month for 2025”).
  2. AI generates SQL that targets your company’s schema and known tables.
  3. Review & edit the SQL in the editable query box.
  4. Run the query to preview results as a table.
  5. Export the current results to JSON or CSV when you’re happy.
The editor supports quick iterations: adjust filters, add GROUP BY, or tweak ORDER BY—then press Run again to refresh the preview.

Schema-Aware by Design

Smart Query uses the tables available in your workspace’s company schema, helping the AI stay aligned with your actual data. This reduces guesswork and speeds up analysis—especially when you’ve just uploaded CSVs or connected external tables.

Editable SQL + Results Preview

After generation, the SQL appears in an editable query box. You stay in control:

  • Change date ranges, add WHERE clauses, or adjust aggregations.
  • Press Run to fetch live results from your workspace data.
  • Preview returns as a tabular view so you can spot-check correctness.
Editable SQL with live results preview in Taptic Data

Editable SQL + results preview. Iterate quickly and keep the best version.

Export Options (JSON & CSV)

When you’ve got the results you need, export them. Smart Query provides quick actions to download the current result set as JSON or CSV, making it easy to share or reuse downstream.

Prompts You Can Try

  • “Monthly sales by region for the past 12 months.”
  • “Top 20 products by total revenue year-to-date.”
  • “Weekly orders trend with average order value.”
  • “Inventory counts by category where quantity < 10.”

Tips for More Accurate Queries

  • Name a table or field when you know it (e.g., orders, order_date, total).
  • Specify time windows like “last quarter,” “YTD,” or “past 30 days.”
  • Be explicit about the breakdown: by month, by region, top N, etc.

Ready to try Smart Query? Head to your workspace and type your first prompt. You’ll have an editable SQL query, results preview, and export options in seconds—no heavy setup required.

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