SAP remains one of the most business-critical yet technically challenging data sources in the enterprise landscape. Highly normalized tables, heterogeneous systems, proprietary interfaces, licensing constraints, and SAP’s ongoing shift toward Business Data Cloud (BDC) all contribute to a demanding integration environment. For organizations adopting hybrid or multi-cloud strategies, SAP integration becomes a structural challenge rather than a routine engineering task.
The latest BARC Spotlight, “Do it the Data Automation Style! – SAP Data Integration in Multi-Cloud Environments” by analyst Timm Grosser, examines how data automation reduces this complexity through metadata-driven modeling and automated code generation. Instead of manually building every data flow, transformation, and structure, data automation tools model them semantically and generate the technical assets automatically - accelerating development, reducing errors, and improving consistency across pipelines.
Why SAP integration remains difficult
SAP continues to serve as the system of record for finance, supply chain, and operations across most large organizations. Deeply normalized table structures require specialist SAP knowledge, licensing rules restrict movement into non-SAP environments, and available APIs often struggle with the throughput required for large-scale analytics workloads. For teams building data lakehouses or modern cloud architectures, these constraints directly influence delivery timelines and total cost of ownership.
Why data automation changes the economics of SAP integration
Manual development of SAP data pipelines leads to: extended delivery cycles, high maintenance burden, and dependence on scarce expertise. Data automation approaches this problem differently by using metadata-driven modeling and automated code generation to reduce repetitive, error-prone work.
The BARC analysis explains how data automation addresses these challenges through metadata-driven modeling and automated code generation. Rather than manually coding each data flow, transformation, and structure, data automation tools generate the necessary technical objects automatically, thereby reducing development time, minimizing errors, and improving consistency across pipelines.
For teams evaluating their strategy, the paper offers a foundation for building a credible business case.
How biGENIUS-X addresses multi-cloud SAP integration
The paper profiles biGENIUS-X as an example of a data automation platform purpose-built for complex source systems such as SAP. It details how the application supports semantic modeling of SAP structures, generates native code for multiple target technologies, and supports governance across distributed environments with its Data Marketplace.
Highlighted functionalities include AI-assisted translation of SAP technical fields into business terms, automated transformation generation, and integrated lineage and documentation, as well as how biGENIUS-X consolidates SAP and non-SAP systems into unified data products for analytics, planning, and AI.
How this report informs your next steps
The BARC Spotlight gives you the analysis needed to:
- Evaluate whether your current SAP integration approach aligns with analytics delivery requirements
- Know how SAP data products can be modeled once and deployed flexibly across Databricks, Snowflake, Microsoft Fabric, and other target environment
- Build a fact-based business case for automation
- Understand where SAP Business Data Cloud fits into your integration strategy, and where it does not
For organizations facing SAP data integration decisions in 2026, this report provides an independent evaluation from a recognized research authority.
Download the full BARC Spotlight
Access the complete BARC Spotlight, “Do it the Data Automation Style! – SAP Data Integration in Multi-Cloud Environments”
