DatriseAI-first ETL

Jira Domo

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

How Datrise loads Jira into Domo

Datrise syncs Jira's issues, sprints, projects, changelogs, and worklog events into Domo as datasets in Domo's cloud store via connector. Flexible or custom fields land in flattened columns for Magic ETL, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses partitioned dataset updates rather than full replaces, so re-runs update only what changed. Domo dataset partitions keyed on load date. Domo stores its own copy of data, so Datrise sends incremental partitions to avoid re-uploading whole datasets.

Ideal for all-in-one cloud BI with built-in ETL.

Endpoints

Jira: Issue tracking for software and operations teams.

Domo: Cloud BI platform combining data integration and executive dashboards.

How Jira entities map to Domo

Jira entityDomo objectNotes
issuesjira_issuesid PK · custom fields → flattened columns for Magic ETL
sprintsjira_sprintsid PK · linked to jira_issues
projectsjira_projectsid PK · linked to jira_issues
changelogsjira_changelogsdate/time columns events

FAQ

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

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

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

It runs incrementally — Datrise uses partitioned dataset updates rather than full replaces.

Related pipelines

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