Local files (Parquet / CSV) test data, inside your network

What works today

Built-in file-set connector for Parquet or CSV extracts in a local or mounted directory (for example a read-only landing zone for exports).

Same engine as the Parquet connector; mount the directory read-only (ro).

Authentication: filesystem permissions.

Capability matrix

Each capability is tracked separately and shown at the level the recorded conformance evidence supports. A connector that only discovers metadata is never presented as equivalent to one that runs the whole workflow.

Read-only proof

Verified from filesystem permissions: the agent user must not be able to write the root.

Conformance evidence

DataNivra runs every connector through a common conformance kit on synthetic data: no write statements, proven read-only access, secret redaction, schema and relationship discovery, bounded streaming, cancellation, clear reason codes, egress canaries and no raw values in logs, then the discover, mask, subset, certify and provision workflow. The published status is computed from those results.

Connector version 0.1.0, last verified 2026-09-30.

What crosses the boundary

Connectors run inside the agent in your network. Only metadata, aggregates and evidence reach DataNivra Cloud:

• Schema, table and column names and data types (for file sets, operator-declared or opaque table names — never data-derived file names).
• Aggregates such as row-count estimates, null and distinct ratios; counts from 1 to 10 are reported as 10 (small-cell protection).
• Classification findings (which column looks like which kind of sensitive data) and relationship metadata.
• Evidence metadata: checksums, gate outcomes, engine and policy versions, and templated error codes.

Never sent:

• Any cell value, row, sample, minimum/maximum or top-k value — masked or not.
• Credentials, connection strings or resolved secret values: DataNivra stores only the secret reference.
• Free text copied from your data, or exception messages that contain values.

See the customer-resident architecture and how to verify these claims yourself.

Setup outline

1. Land Parquet or CSV extracts in a directory and mount it read-only into the agent container.
2. For CSV, declare whether files have a header row (has_header) — discovery refuses to guess.
3. Declare the tables you want, or rely on opaque names; store the connection document in your secret store.
4. In the console, register the source with the secret reference of that document (for example vault://tdm/source-connection) and the agent that can reach it, then run discovery.

Example connection document, stored in your secret store and resolved by the agent locally (DataNivra only ever sees its reference):

{
  "kind": "LOCAL_FILES",
  "root": "/data/landing",
  "format": "csv",
  "has_header": true,
  "tables": { "customers": "customers.csv", "accounts": "accounts.csv" }
}

Next: install the agent, then follow the getting started guide.