The ‘Zero-Copy’ Reality: Bi-Directional Federation with SAP Business Data Cloud and BigQuery

For years, SAP customers pursuing advanced analytics and AI have faced a familiar tradeoff: move data out of SAP to enable innovation or keep it in place to preserve governance and performance. Traditional extract, transform, and load (ETL) pipelines solved the access problem but introduced new challenges around latency, duplication, cost, and data consistency. As data volumes grow and AI workloads demand fresher information, many organizations are questioning whether heavy data movement still makes sense.

SAP and Google Cloud are positioning bi-directional zero-copy federation between SAP Business Data Cloud (BDC) and Google BigQuery as a practical alternative. Rather than copying data between systems, this approach allows SAP data to be queried directly in BigQuery for analytics and AI, while BigQuery data can be accessed from SAP applications for planning and operational decision-making, without physically moving the data.

From One-Way Access to Bi-Directional Federation

Early zero-copy integrations largely focused on one direction: exposing SAP data to external analytics platforms. With SAP Business Data Cloud and BigQuery, SAP customers can now federate data in both directions. SAP transactional and analytical data can be queried from BigQuery using native connectors, enabling data scientists to train models or run large-scale analytics without replicating sensitive ERP data.

At the same time, BigQuery datasets can be accessed from SAP environments. This allows planning, finance, and supply chain teams to consume external insights directly within SAP applications without having to ingest or duplicate them. For example, a demand forecast generated in BigQuery can be referenced by SAP Integrated Business Planning or analytics tools as if it were local data.

This bi-directional capability reflects a broader shift in enterprise data architecture. Instead of centralizing all data in a single warehouse or lake, organizations are increasingly adopting federated data fabrics that emphasize access, governance, and interoperability over ownership.

Why Zero-Copy Matters

The business case for zero-copy federation extends beyond architectural elegance. Eliminating large-scale data movement reduces storage costs, minimizes synchronization delays, and lowers operational risk. For AI workloads, where model accuracy depends on current data, querying SAP systems directly helps avoid stale insights caused by batch-based ETL processes.

SAP Business Data Cloud plays a central role by preserving SAP’s business semantics, security model, and authorizations, even when data is accessed externally. Google BigQuery, in turn, provides scalable analytics and AI capabilities optimized for complex queries and machine learning workloads. Together, they allow organizations to align AI experimentation with enterprise-grade governance.

The bi-directional nature of the integration is particularly important for planning use cases. Historically, insights generated outside SAP often had to be reloaded into SAP systems before they could influence operational decisions. Zero-copy federation shortens this loop, allowing planning teams to react more quickly to market changes while maintaining a single source of truth.

What This Means for SAPinsiders

ETL-heavy SAP data pipelines are no longer the default. Bi-directional zero-copy federation reduces duplication and latency by enabling direct access across platforms. Teams adopting similar approaches report faster analytics delivery and lower data engineering overhead. This change also lowers the risk of data drift between SAP systems and downstream analytics environments.

AI and planning can finally share the same data foundation. BigQuery-powered AI models can operate on live SAP data, while SAP planning tools can consume external insights without ingestion delays. Technology leaders should evaluate performance, security enforcement, and semantic consistency when comparing federation options. Latency tolerance and workload isolation are especially important when mixing AI queries with operational planning processes.

Data architecture decisions will reshape daily SAP operations. Zero-copy approaches shift effort from pipeline maintenance to access governance and performance tuning. Successful adopters typically start with high-value analytics or planning scenarios before expanding federation across broader SAP domains. Over time, this enables leaner data teams and tighter collaboration between SAP, analytics, and AI stakeholders.