DatriseAI-first ETL

Front to Microsoft Power BI Integration

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

How Datrise loads Front into Microsoft Power BI

Datrise syncs Front's conversations, messages, contacts, inboxes, tags, and teammates 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

Front: Shared inbox for team email and messaging.

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

How Front entities map to Microsoft Power BI

Front entityMicrosoft Power BI objectNotes
conversationsfrontapp_conversationsid PK · custom fields → flattened columns (nested fields expanded)
messagesfrontapp_messagesid PK · linked to frontapp_conversations
contactsfrontapp_contactsid PK · linked to frontapp_conversations
inboxesfrontapp_inboxesid PK · linked to frontapp_conversations

FAQ

How does Datrise handle Front'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 Front 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

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