Lakehouse Analytics Fed by iDataEngine addresses a problem most SAP landscapes know too well: Fabric investments idle when SAP feeds are late, opaque, or manually rebuilt.
CTM (Cloud Transfer Module) loads SAP-driven datasets into Microsoft Fabric / OneLake with connection vault, structured paths, job history, and incremental watermarks.
Fabric connections are maintained once; SQL and REP pipelines can target the lake by name — same monitoring habits as on-prem SQL Transfer.
Capabilities you use in iDataEngine
- CTM in Advanced/Platinum plans
- Load statistics dashboard
- Health probe on connections
- Incremental watermark resume
- Structured Data Lake loads
- Target path templates
Recommended workflow
- Run Test (iDataView Test, SQL First Row, API Test Service, or AG scan) before scheduling or publishing.
- Open the relevant cockpit (iDataView Explorer, SQL Project, API Service Detail, or AccessGuard).
- Enable monitoring alerts and review dashboard KPIs for the first production cycle.
- Save and capture the generated URL, job ID, or snapshot reference in your change record.
Real-world scenario (2025)
Controlling loads actuals from SAP into OneLake for Power BI enterprise datasets — CTM job history proves refresh for audit.
Why it matters
Analytics on OneLake only matter if SAP operational truth arrives on schedule — CTM is that bridge.
Measured on lead time, defect rate, and audit readiness, the platform pays back in the first production quarter.