DatriseAI-first ETL

Jira Yellowfin

AI-first ETL from Jira into Yellowfin. Governed entities, incremental sync, typed landing tables.

How Datrise loads Jira into Yellowfin

Datrise syncs Jira's issues, sprints, projects, changelogs, and worklog events into Yellowfin as warehouse tables Yellowfin builds views on. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.

Ideal for dashboards with automated data storytelling.

Endpoints

Jira: Issue tracking for software and operations teams.

Yellowfin: BI suite with dashboards, automated insights, and data storytelling.

How Jira entities map to Yellowfin

Jira entityYellowfin objectNotes
issuesjira_issuesid PK · custom fields → flattened columns
sprintsjira_sprintsid PK · linked to jira_issues
projectsjira_projectsid PK · linked to jira_issues
changelogsjira_changelogsdate/time dimensions events

FAQ

How does Datrise handle Jira's custom fields in Yellowfin?

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 Yellowfin types.

How does the Jira to Yellowfin sync stay up to date?

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

Related pipelines

Early access

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