DatriseAI-first ETL

My Hours Chartio

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

How Datrise loads My Hours into Chartio

Datrise syncs My Hours's records, events, and configuration objects 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

My Hours: SaaS or API data source for analytics and warehouse sync.

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

How My Hours entities map to Chartio

My Hours entityChartio objectNotes
recordsmy_hours_recordsid PK · custom fields → flattened columns for visual SQL
eventsmy_hours_eventstemporal columns events
configuration objectsmy_hours_configuration_objectsid PK · linked to my_hours_records

FAQ

How does Datrise handle My Hours'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 My Hours to Chartio sync stay up to date?

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

Related pipelines

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