DatriseAI-first ETL

GitHub Webhook to Holistics Integration

AI-first ETL from GitHub Webhook into Holistics. Governed entities, incremental sync, typed landing tables.

How Datrise loads GitHub Webhook into Holistics

Datrise syncs GitHub Webhook's push events, pull requests, issues, releases, commits, and workflow runs into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.

Ideal for as-code BI modeling on a warehouse.

Endpoints

GitHub Webhook: Repository event stream delivered by webhook.

Holistics: Self-service BI with modeling layers and scheduled report delivery.

How GitHub Webhook entities map to Holistics

GitHub Webhook entityHolistics objectNotes
push eventsgithub_webhook_push_eventsdate/time dimensions events
pull requestsgithub_webhook_pull_requestsid PK · linked to github_webhook_push_events
issuesgithub_webhook_issuesid PK · linked to github_webhook_push_events
releasesgithub_webhook_releasesid PK · linked to github_webhook_push_events

FAQ

How does Datrise handle GitHub Webhook's custom fields in Holistics?

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

How does the GitHub Webhook to Holistics sync stay up to date?

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

Related pipelines

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