DatriseAI-first ETL

StackAdapt to ThoughtSpot Integration

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

How Datrise loads StackAdapt into ThoughtSpot

Datrise syncs StackAdapt's campaigns, line items, creatives, spend, impressions, and conversions 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

StackAdapt: Programmatic advertising across native and display.

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

How StackAdapt entities map to ThoughtSpot

StackAdapt entityThoughtSpot objectNotes
campaignsstackadapt_campaignsid PK · custom fields → flattened columns for searchable fields
line itemsstackadapt_line_itemsid PK · linked to stackadapt_campaigns
creativesstackadapt_creativesid PK · linked to stackadapt_campaigns
spendstackadapt_spendid PK · linked to stackadapt_campaigns

FAQ

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

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

Related pipelines

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