SAP S/4HANA data flows into Google Cloud Platform via dual-path ingestion using Cloud Dataflow for batch and Cloud Pub/Sub for streaming, feeding a multi-tier BigQuery data lake architecture. ETL processing stages—row-level transform, cleansing, conformance, and aggregation—progressively refine data across raw, curated, and aggregated tiers, with Dataplex providing unified governance and metadata management. AI-assisted development through Gemini AI and GitHub Copilot accelerates transformation logic and semantic modeling, while the serving layer exports business-ready facts and dimensions to Power BI's semantic model for analytics. This architecture demonstrates modern cloud-native ELT patterns with built-in AI acceleration, enabling organizations to modernize legacy SAP systems with scalable, governed data pipelines. Fork and customize this diagram on Diagrams.so to adapt ingestion patterns, tier definitions, or AI tooling to your enterprise requirements.