DatriseAI-first ETL

Ploomes to Amazon QuickSight Integration

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

How Datrise loads Ploomes into Amazon QuickSight

Datrise syncs Ploomes's contacts, companies, deals, quotes, products, and pipeline stages 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

Ploomes: CRM with quoting and product catalogs for Brazilian sales.

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

How Ploomes entities map to Amazon QuickSight

Ploomes entityAmazon QuickSight objectNotes
contactsploomes_contactsid PK · custom fields → flattened columns for analyses
companiesploomes_companiesid PK · linked to ploomes_contacts
dealsploomes_dealsid PK · linked to ploomes_contacts
quotesploomes_quotesid PK · linked to ploomes_contacts

FAQ

How does Datrise handle Ploomes'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 Ploomes 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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