DatriseAI-first ETL

Datascope to Redash Integration

AI-first ETL from Datascope into Redash. Governed entities, incremental sync, typed landing tables.

How Datrise loads Datascope into Redash

Datrise syncs Datascope's forms, submissions, users, locations, attachments, and answers into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

Datascope: Mobile forms for field data capture.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Datascope entities map to Redash

Datascope entityRedash objectNotes
formsdatascope_formsid PK · custom fields → flattened columns for query results
submissionsdatascope_submissionsid PK · linked to datascope_forms
usersdatascope_usersid PK · linked to datascope_forms
locationsdatascope_locationsid PK · linked to datascope_forms

FAQ

How does Datrise handle Datascope's custom fields in Redash?

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

How does the Datascope to Redash sync stay up to date?

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

Related pipelines

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