DatriseAI-first ETL

Chartmogul ThoughtSpot

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

How Datrise loads Chartmogul into ThoughtSpot

Datrise syncs Chartmogul's records, events, and configuration objects 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

Chartmogul: SaaS or API data source for analytics and warehouse sync.

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

How Chartmogul entities map to ThoughtSpot

Chartmogul entityThoughtSpot objectNotes
recordschartmogul_recordsid PK · custom fields → flattened columns for searchable fields
eventschartmogul_eventsdate/time columns events
configuration objectschartmogul_configuration_objectsid PK · linked to chartmogul_records

FAQ

How does Datrise handle Chartmogul'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 Chartmogul to ThoughtSpot sync stay up to date?

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

Related pipelines

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