The Microsoft analytics estate end to end: semantic models designed for scale, DAX that survives real data volumes, workspace and capacity governance, deployment pipelines, and the medallion architecture underneath - Lakehouse, Warehouse and Dataflows Gen2 - orchestrated in Fabric.
The transformation layer between raw source and reported number: star schemas at the right grain, KPI logic encoded at the data layer, everything tested, documented and version-controlled with CI - dbt-style discipline whatever the platform underneath.
Ingestion, pipelines and orchestration on enterprise cloud platforms: batch and streaming sources, PySpark at scale, secrets and identity handled properly, environments promoted through code. The plumbing every layer above depends on.
Runs a reporting estate as a product: standards and governance, workspace and capacity management, stakeholder cadence, and the consolidation and migration programs every mature estate eventually needs.
End-to-end platform architecture: platform selection and integration patterns, security and governance design, operational data integration - including SAP PM - and roadmaps that hold from procurement through production.