DatriseAI-first ETL

Insightly Amazon QuickSight

AI-first ETL from Insightly into Amazon QuickSight. Governed entities, incremental sync, typed landing tables.

How Datrise loads Insightly into Amazon QuickSight

Datrise syncs Insightly's contacts, organizations, opportunities, projects, and delivery milestones into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Insightly: CRM and lightweight project delivery.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Insightly entities map to Amazon QuickSight

Insightly entityAmazon QuickSight objectNotes
contactsinsightly_contactsid PK · custom fields → flattened columns for analyses
organizationsinsightly_organizationsid PK · linked to insightly_contacts
opportunitiesinsightly_opportunitiesid PK · linked to insightly_contacts
projectsinsightly_projectsid PK · linked to insightly_contacts

FAQ

How does Datrise handle Insightly's custom fields in Amazon QuickSight?

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

How does the Insightly to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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