DatriseAI-first ETL

Sailthru to Microsoft Power BI Integration

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

How Datrise loads Sailthru into Microsoft Power BI

Datrise syncs Sailthru's users, campaigns, blasts, message events, lists, and content items 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

Sailthru: Personalized email and onsite content targeting.

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

How Sailthru entities map to Microsoft Power BI

Sailthru entityMicrosoft Power BI objectNotes
userssailthru_usersid PK · custom fields → flattened columns (nested fields expanded)
campaignssailthru_campaignsid PK · linked to sailthru_users
blastssailthru_blastsid PK · linked to sailthru_users
message eventssailthru_message_eventsdate/time columns with a date table events

FAQ

How does Datrise handle Sailthru'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 Sailthru 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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