DatriseAI-first ETL

Gong to Amazon QuickSight Integration

AI-first ETL from Gong into Amazon QuickSight. Governed entities, incremental sync, typed landing tables.

How Datrise loads Gong into Amazon QuickSight

Datrise syncs Gong's calls, transcripts, deals, users, trackers, and call topics into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Gong: Revenue intelligence from recorded sales calls.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Gong entities map to Amazon QuickSight

Gong entityAmazon QuickSight objectNotes
callsgong_callsid PK · custom fields → flattened columns for analyses
transcriptsgong_transcriptsid PK · linked to gong_calls
dealsgong_dealsid PK · linked to gong_calls
usersgong_usersid PK · linked to gong_calls

FAQ

How does Datrise handle Gong's custom fields in Amazon QuickSight?

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

How does the Gong to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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