One Data

Our new paper explains how a dedicated intelligence layer fills that gap with data contracts, health dashboards, and automated lineage, so every data product meets the same trust bar regardless of whether it’s SAP-managed or custom-built.

Migrating BW to Business Data Cloud? Every custom report and calculation needs converting... Our paper shows how automated structural analysis pinpoints what to keep and translates it into ready-to-deploy Datasphere models.

Our paper explains how a Model-as-Code framework with Git-based versioning, pull-request reviews, and automated logic checks brings real software engineering discipline to your Datasphere models, so they are tested and promoted safely across environments.

Our new paper explains how a dedicated intelligence layer fills that gap with data contracts, health dashboards, and automated lineage, so every data product meets the same trust bar regardless of whether it’s SAP-managed or custom-built.

SAP data doesn’t exist in isolation. It’s often combined with data from Snowflake, Databricks, and cloud data lakes. A governance approach that only covers SAP can leave gaps for downstream consumers and AI applications. Our new paper shows how automated column-level lineage and an AI-powered business glossary can help bring SAP and non-SAP data products under one governance framework.

SAP BDC lets you register data products. But who enforces quality, monitors freshness, and traces lineage? We mapped exactly where that gap sits and how a combination of active data contracts with binding SLAs, continuous health monitoring, and cross-system column-level lineage closes it. New paper out now.