DatriseAI-first ETL

Vtiger Microsoft Power BI

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

How Datrise loads Vtiger into Microsoft Power BI

Datrise syncs Vtiger's sales, support, and lifecycle workflows in a unified CRM model 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

Vtiger: Unified CRM for sales, help desk, and customer lifecycle workflows.

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

How Vtiger entities map to Microsoft Power BI

Vtiger entityMicrosoft Power BI objectNotes
salesvtiger_salesid PK · custom fields → flattened columns (nested fields expanded)
supportvtiger_supportid PK · linked to vtiger_sales
lifecycle workflows in a unified CRM modelvtiger_lifecycle_workflows_in_a_unified_crm_modelid PK · linked to vtiger_sales

FAQ

How does Datrise handle Vtiger'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 Vtiger 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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