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Data Console: Browsing a Database Safely

The usual way to answer a data question is a shared read-only login, which grants everything to everyone and audits nothing. The Data Console is the alternative: people browse the tables they are allowed to browse, sensitive columns come back masked unless someone has been granted otherwise, and every access is recorded.

Before you start

  • A data source connected with read-only credentials.
  • A sensitivity scan run, so PII columns are known before anyone browses.
  • A view on who should be able to unmask what — the default is nobody.

Steps

  1. 1

    Open Data Console from the product switcher and connect a data source (read-only credentials recommended)

  2. 2

    The schema loads automatically — browse tables, filter and search rows, follow foreign keys with one click

  3. 3

    Run the sensitivity scan so PII columns are flagged and masked for anyone without an unmask grant

  4. 4

    Share the source with teammates read-only; grant unmask rights per column only where justified

  5. 5

    Use Access Review for a CSV report of who can browse and who can unmask, across every source

  6. 6

    Need staging data? Generate a masked, FK-intact test-data copy instead of sharing production

What goes wrong

Masking is default-deny

A column identified as sensitive is masked until someone is granted the right to see it. A new column that looks sensitive is masked before anyone decides, rather than exposed until someone notices.

Grouping by a masked column is refused

Aggregating on a masked column can reconstruct the values it was meant to hide — a small group is an identification. Such queries are rejected rather than answered with a hint.

Access Review is the report to run before an audit

It answers 'who can see what' across every source in one CSV. That question is very hard to answer from a pile of database grants, and it is the one auditors ask first.

Next

Data Console: Asking Questions in Plain English

Ask questions of your data in plain language, using your own AI provider key, with every lookup shown and audited.

Reusable Masking Policies

Define masking rules once and apply them across projects, with deterministic values that keep joins working.

Agent Gateway: Connecting an AI Agent

Give an AI agent a scoped, audited door into a database — structured tools instead of raw SQL, with writes gated behind approval.