The unified data layer connecting SAP S/4HANA, SAP BW, and non-SAP sources. We implement the business semantic model, data products, and federation layer so your analytics reflects the full business picture, not just what lives inside SAP.
Lakehouse architecture for enterprises running large-scale analytics, ML, and AI workloads alongside SAP. We design the medallion architecture, build ingestion pipelines from SAP and operational systems, and connect Databricks to the enterprise BI layer.
Cloud data warehouse implementation and migration for enterprises consolidating on Google Cloud or a multi-cloud stack. Data modeling, pipeline build, and integration with SAP and third-party source systems.
ETL and ELT pipelines connecting SAP, operational databases, SaaS applications, and IoT sources into the target platform. Built with the data contracts and quality controls that make downstream AI and analytics reliable.
SAP Analytics Cloud and Power BI implementation on top of the modernized data platform. Finance planning models, operational dashboards, and executive reporting built on one version of the truth.
SAP MDG implementation and data quality frameworks that keep the platform clean over time. Master data governance is not a one-time exercise. We build the process and tooling to sustain it.
The ECC data warehouse no longer fits. The new platform needs to be designed alongside the SAP program, not as a post-go-live afterthought.
AI agents and predictive models require clean, governed, connected data. Most enterprises discover the data gap after the AI pilot, not before. We fix the foundation.
Multiple platforms, inconsistent semantics, no single source of truth. Finance, operations, and supply chain all work from different numbers. The business has lost confidence in its own data.