GitHub → GoodData
AI-first ETL from GitHub into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads GitHub into GoodData
Datrise syncs GitHub's repositories, issues, pull requests, commits, and workflow runs into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.
Ideal for embedded, multi-tenant analytics.
Endpoints
GitHub: Developer platform for repos, issues, and delivery workflows.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How GitHub entities map to GoodData
| GitHub entity | GoodData object | Notes |
|---|---|---|
| repositories | github_repositories | id PK · custom fields → flattened columns |
| issues | github_issues | id PK · linked to github_repositories |
| pull requests | github_pull_requests | id PK · linked to github_repositories |
| commits | github_commits | id PK · linked to github_repositories |
FAQ
How does Datrise handle GitHub's custom fields in GoodData?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native GoodData types.
How does the GitHub to GoodData sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
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