DatriseAI-first ETL

MoEngage Looker

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

How Datrise loads MoEngage into Looker

Datrise syncs MoEngage's engagement events, campaign performance, and retention behavior signals into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.

Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.

Ideal for governed, version-controlled BI on a warehouse.

Endpoints

MoEngage: Customer engagement source for campaigns and retention metrics.

Looker: Google Cloud BI with LookML semantic models and governed dashboards.

How MoEngage entities map to Looker

MoEngage entityLooker objectNotes
engagement eventsmoengage_engagement_eventsdate/time dimension columns 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 Looker?

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

How does the MoEngage to Looker sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.

Related pipelines

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