Pagerduty to Looker Studio Integration
AI-first ETL from Pagerduty into Looker Studio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Pagerduty into Looker Studio
Datrise syncs Pagerduty's incidents, services, schedules, escalation policies, log entries, and responders 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
Pagerduty: Incident response, on-call schedules, and escalation.
Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).
How Pagerduty entities map to Looker Studio
| Pagerduty entity | Looker Studio object | Notes |
|---|---|---|
| incidents | pagerduty_incidents | id PK · custom fields → flattened columns for chart fields |
| services | pagerduty_services | id PK · linked to pagerduty_incidents |
| schedules | pagerduty_schedules | id PK · linked to pagerduty_incidents |
| escalation policies | pagerduty_escalation_policies | id PK · linked to pagerduty_incidents |
FAQ
How does Datrise handle Pagerduty'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 Pagerduty to Looker Studio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
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Early access
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