From Data Silos to Enterprise AI with SAP, AWS and Snowflake

The Problem
Enterprises run their most critical business processes on SAP, but that data rarely reaches the teams and systems that need it most. Combining SAP and non-SAP sources, IoT signals, and unstructured content into a single, AI-ready environment has meant complex pipelines, duplicated data, and slow time to insight. The technology to solve this now exists and it runs on infrastructure your organisation likely already trusts.

The Solution
SAP Business Data Cloud, Snowflake, and AWS form a co-engineered path to Enterprise AI. SAP remains the system of record. Snowflake becomes the system of intelligence, bringing SAP data products from S/4HANA into a governed, queryable environment via zero-copy integration: no ETL, with full SAP business semantics preserved. AWS provides the enterprise-grade infrastructure and GPU compute that powers it all, including access to leading AI models such as Anthropic via Amazon Bedrock. Three platforms, working as one.

What You Will Learn

• How to bring SAP S/4HANA data products into Snowflake in minutes, with business semantics intact and no ETL pipeline

• Live demo: combining SAP Plant Maintenance data, shop floor IoT sensor data, and unstructured documents to pinpoint a manufacturing root cause in minutes, a task that previously took days or weeks

• How AI inference runs on AWS GPU infrastructure, with support for leading models including Anthropic via Amazon Bedrock

• A practical adoption path: preserve stable systems, introduce zero-copy for new use cases, validate with analytics and AI, then scale

• How to get started: joint SAP and Snowflake workshops, trials, and hands-on lab access with a QR code to take home

Who This Is For
CDOs, VPs of Data, BI/Analytics leads, and data architects at enterprises running SAP BW who are planning their next platform step, evaluating SAP Business Data Cloud, or looking to unlock AI on their SAP data estate, on AWS infrastructure.