DatriseAI-first ETL

Ploomes Microsoft Power BI

AI-first ETL from Ploomes into Microsoft Power BI. Governed entities, incremental sync, typed landing tables.

How Datrise loads Ploomes into Microsoft Power BI

Datrise syncs Ploomes's contacts, accounts, deals, activities, and lifecycle events into Microsoft Power BI as star-schema-friendly tables for an Import or DirectQuery dataset. Flexible or custom fields land in flattened columns (nested fields expanded), and timestamps such as created, updated, and status changes are typed as date/time columns with a date table.

Sync is incremental: Datrise uses incremental-refresh windows aligned to Power BI's RangeStart/RangeEnd, so re-runs update only what changed. Date-partitioned fact tables matching incremental-refresh policies. Power BI measures and relationships live in the .pbix model, so Datrise keeps the underlying tables stable and star-schema-shaped.

Ideal for Microsoft-stack self-serve reporting.

Endpoints

Ploomes: CRM widely used in Latin America for sales pipeline and customer ops.

Microsoft Power BI: Microsoft business intelligence with datasets, reports, and semantic models.

How Ploomes entities map to Microsoft Power BI

Ploomes entityMicrosoft Power BI objectNotes
contactsploomes_contactsid PK · custom fields → flattened columns (nested fields expanded)
accountsploomes_accountsid PK · linked to ploomes_contacts
dealsploomes_dealsid PK · linked to ploomes_contacts
activitiesploomes_activitiesdate/time columns with a date table events

FAQ

How does Datrise handle Ploomes's custom fields in Microsoft Power BI?

Flexible values are stored as flattened columns (nested fields expanded), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft Power BI types.

How does the Ploomes to Microsoft Power BI sync stay up to date?

It runs incrementally — Datrise uses incremental-refresh windows aligned to Power BI's RangeStart/RangeEnd.

Related pipelines

Early access

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