DatriseAI-first ETL

MoEngage Amazon QuickSight

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

How Datrise loads MoEngage into Amazon QuickSight

Datrise syncs MoEngage's engagement events, campaign performance, and retention behavior signals 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

MoEngage: Customer engagement source for campaigns and retention metrics.

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

How MoEngage entities map to Amazon QuickSight

MoEngage entityAmazon QuickSight objectNotes
engagement eventsmoengage_engagement_eventsdate/time fields events
campaign performancemoengage_campaign_performanceid PK · linked to moengage_engagement_events
retention behavior signalsmoengage_retention_behavior_signalsid PK · linked to moengage_engagement_events

FAQ

How does Datrise handle MoEngage'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 MoEngage 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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