DatriseAI-first ETL

Datascope to Chartio Integration

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

How Datrise loads Datascope into Chartio

Datrise syncs Datascope's forms, submissions, users, locations, attachments, and answers into Chartio as SQL tables a visual-SQL explorer connects to. Flexible or custom fields land in flattened columns for visual SQL, 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. Visual-SQL tools build joins from your schema, so Datrise lands clearly related tables with stable id columns.

Ideal for drag-and-drop charting over a database.

Endpoints

Datascope: Mobile forms for field data capture.

Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.

How Datascope entities map to Chartio

Datascope entityChartio objectNotes
formsdatascope_formsid PK · custom fields → flattened columns for visual SQL
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 Chartio?

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

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

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

Related pipelines

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