DatriseAI-first ETL

Urban Airship to ThoughtSpot Integration

AI-first ETL from Urban Airship into ThoughtSpot. Governed entities, incremental sync, typed landing tables.

How Datrise loads Urban Airship into ThoughtSpot

Datrise syncs Urban Airship's push notifications, channels, audiences, message events, segments, and named users into ThoughtSpot as warehouse tables ThoughtSpot indexes for search. Flexible or custom fields land in flattened columns for searchable fields, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the indexed tables, so re-runs update only what changed. Date-partitioned facts for live-query performance. ThoughtSpot search relies on clear names and relationships, so Datrise lands well-named, joinable tables.

Ideal for natural-language search analytics over a warehouse.

Endpoints

Urban Airship: Mobile push and cross-channel message orchestration.

ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.

How Urban Airship entities map to ThoughtSpot

Urban Airship entityThoughtSpot objectNotes
push notificationsurban_airship_push_notificationsid PK · custom fields → flattened columns for searchable fields
channelsurban_airship_channelsid PK · linked to urban_airship_push_notifications
audiencesurban_airship_audiencesid PK · linked to urban_airship_push_notifications
message eventsurban_airship_message_eventsdate/time columns events

FAQ

How does Datrise handle Urban Airship's custom fields in ThoughtSpot?

Flexible values are stored as flattened columns for searchable fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native ThoughtSpot types.

How does the Urban Airship to ThoughtSpot sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the indexed tables.

Related pipelines

Early access

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