DatriseAI-first ETL

Intruder to Looker Studio Integration

AI-first ETL from Intruder into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Intruder into Looker Studio

Datrise syncs Intruder's scans, issues, targets, severities, occurrences, and remediation statuses into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Intruder: Continuous vulnerability scanning for internet assets.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Intruder entities map to Looker Studio

Intruder entityLooker Studio objectNotes
scansintruder_scansid PK · custom fields → flattened columns for chart fields
issuesintruder_issuesid PK · linked to intruder_scans
targetsintruder_targetsid PK · linked to intruder_scans
severitiesintruder_severitiesid PK · linked to intruder_scans

FAQ

How does Datrise handle Intruder's custom fields in Looker Studio?

Flexible values are stored as flattened columns for chart fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker Studio types.

How does the Intruder to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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