Unlocking SAP data for AI transformation

For large enterprises, SAP is the backbone of finance, supply chain, manufacturing, and HR. Yet, even with investments in modern data platforms and AI, organizations struggle to unlock the full value of their SAP data. Why?

• Poor data quality and trust: This is one of the most frequent challenges organizations cite as the main barrier to extracting value from data

• Siloed and fragmented data: SAP data is often disconnected from the rest of the enterprise, making holistic analysis difficult

• Complex integrations: Building and maintaining data pipelines drains time, resources, and budgets

• Loss of business context: Data frequently loses its meaning when extracted from SAP, reducing its usefulness for analytics and AI

• Limited AI potential: Many AI initiatives overlook SAP data due to access issues and lack of scalable infrastructure

• High data management costs: Hidden expenses from data duplication and maintenance quickly add up

• Legacy modernization challenges: On-premise SAP systems (like Business Warehouse and ERP Central Component) are hard to scale and modernize for today's needs

   

These challenges are increasingly unsustainable in a world where speed, trust, and intelligence are everything.

The SAP Databricks partnership is a strategic integration designed to make SAP data accessible, usable, and valuable within the open Lakehouse architecture.

• Direct, governed access: Access SAP data directly from Databricks, governed by Unity Catalog for enterprise-grade security

• Preserved business semantics: Maintain SAP's complex metadata, logic, and business context, including Core Data Services views and hierarchies

• Simplified integration: Real-time and batch pipelines are streamlined with zero-copy data integration using Delta Sharing

• AI/ML enablement: Build predictive models, LLM-powered copilots, and intelligent apps directly on SAP data using Databricks' AI/ML tools

• Unified architecture: Combine SAP and non-SAP data (for example, Salesforce, IoT) in a single Lakehouse platform, eliminating silos

• Enterprise-grade governance: Govern SAP data access down to the column level, across regions and business units

   

With SAP Databricks, organizations can finally start to break down the SAP data barrier and operationalize insights across business workflows. This can help accelerate AI delivery, get closer to customers, and reduce costs.

SAP Databricks lays the foundational capabilities for agentic AI initiatives. Through direct, governed access and the preservation of complex SAP business semantics, organizations can enable their agents to operate on accurate, context-rich information. The combination of SAP and non-SAP data, along with a reduction of data silos, provides the holistic view essential for building intelligent agents that can autonomously analyze, predict, and act based on available data. These agents could help organizations:

• Automate supply chain responses by detecting disruptions and rerouting shipments in real time

• Optimize inventory by forecasting demand and triggering restocking processes autonomously

• Personalize customer engagement by adapting offers and communications based on live transaction and behavioral data

• Monitor financial transactions to identify fraud and initiate preventive measures without human intervention

• Manage workforce scheduling and resource allocation by analyzing operational needs and dynamically adjusting plans
   

By enabling these intelligent, self-directed workflows, organizations can drive operational efficiency, proactive decision-making, and innovation across business processes.

Here's our advice on how to approach the SAP Databricks implementation.

• Assess your SAP data landscape: Identify where your SAP data sits, how it's currently used, and the main pain points

• Engage stakeholders early: Bring together business and technology teams to align on goals and challenges

• Start small, scale fast: Pilot SAP Databricks on a high-impact use case, such as predictive analytics or real-time dashboards, then expand

• Prioritize governance: Use Unity Catalog to enhance data security and support compliance

• Partner with experts: Work with teams who understand both SAP and Databricks to accelerate integration and value realization

   

As organizations look to unlock more value from their SAP data, the SAP Databricks partnership offers a practical path forward. By addressing long-standing challenges around data quality, integration, and AI enablement, this approach can help enterprises make better use of their information assets. Starting with a clear assessment of the current SAP data landscape, engaging stakeholders, and piloting high-impact use cases can lay the groundwork for sustainable transformation and the new possibilities offered by agentic AI.