SAP Business Data Cloud Connect for BigQuery Reaches General Availability, Bringing Zero-Copy Data Access to Enterprise AI

SAP and Google Cloud Bring Zero-Copy Enterprise Data to AI

Artificial intelligence is transforming how organizations analyze information, automate operations, and make business decisions. However, one major obstacle continues to slow enterprise AI adoption: fragmented data spread across multiple business systems.

Enterprise information often resides in ERP platforms, cloud data warehouses, operational databases, customer applications, and analytics environments. Before AI applications can use this data, organizations typically spend weeks or even months building data pipelines that copy, transform, and synchronize information between systems.

This traditional approach increases infrastructure costs, creates duplicate copies of business data, complicates governance, and often leaves AI applications working with outdated information.

To address these challenges, SAP and Google Cloud have announced the general availability (GA) of SAP Business Data Cloud Connect for BigQuery, introducing a secure zero-copy architecture that enables organizations to access enterprise data where it already resides.

Rather than replicating business information across multiple platforms, the integration enables organizations to securely query live SAP data from BigQuery while preserving business semantics, governance policies, and security controls. According to the companies, this provides a stronger foundation for enterprise analytics, generative AI, and agentic AI applications.

The announcement marks the next phase of the long-standing partnership between SAP and Google Cloud, bringing together SAP Business Data Cloud, BigQuery, Knowledge Catalog (formerly Dataplex), Gemini Enterprise, and SAP Joule into a connected enterprise data ecosystem.

Why Traditional Enterprise Data Architecture Slows AI

Modern enterprises generate massive amounts of operational data every day.

Financial platforms process transactions, manufacturing systems monitor production, supply chain applications track inventory, customer platforms capture interactions, and HR systems manage workforce information.

Although this data is critical for business operations, it often exists in disconnected environments.

Organizations have traditionally relied on Extract, Transform, and Load (ETL) pipelines to copy enterprise data into centralized repositories before analytics platforms and AI applications can access it.

While this approach has supported business intelligence for many years, it introduces several challenges for AI workloads.

Organizations commonly face:

• Multiple copies of the same business data

• Data synchronization delays

• Higher storage and infrastructure costs

• Increased governance complexity

• Slower AI development cycles

• Greater operational overhead

Traditional reporting systems can tolerate data delays. AI applications and intelligent agents, however, require immediate access to trusted, up-to-date business information to generate accurate insights and automate complex workflows.

Google Cloud and SAP believe reducing these data challenges is essential for organizations looking to scale enterprise AI successfully.

What Is SAP Business Data Cloud Connect for BigQuery?

SAP Business Data Cloud Connect for BigQuery establishes a secure, bidirectional connection between SAP Business Data Cloud and Google BigQuery.

Instead of moving enterprise information into another storage platform, organizations can securely query live business data while it remains in its original environment.

This zero-copy architecture preserves:

• Business context

• Semantic relationships

• Metadata

• Governance policies

• Security controls

• Data freshness

The integration goes beyond traditional data sharing.

SAP business tables, metadata, and business semantics become directly accessible within Google's data and AI ecosystem through BigQuery and Knowledge Catalog. Likewise, organizations can securely access Google Cloud data from SAP Business Data Cloud without creating duplicate datasets.

According to Google Cloud, this allows AI systems to understand business relationships instead of working with isolated database fields.

For example, AI applications can recognize relationships between purchase orders, suppliers, inventory, manufacturing operations, financial transactions, and customer information rather than interpreting disconnected records.

This richer business context enables AI systems to generate more accurate insights, recommendations, and automated business actions.

Building AI on Trusted Business Data

One of the biggest advantages of SAP Business Data Cloud Connect for BigQuery is its ability to provide AI applications with trusted, semantically rich enterprise information.

Large language models become significantly more useful when they understand not only raw data but also the business meaning behind that information.

SAP Business Data Cloud preserves this semantic context through business metadata, allowing Google's AI ecosystem to operate using business-aware information rather than isolated database records.

According to SAP and Google Cloud, this helps organizations build more reliable AI applications while maintaining enterprise governance.

The integration enables organizations to:

• Build AI on trusted enterprise data

• Develop intelligent multi-agent workflows

• Improve conversational business analytics

• Deliver context-aware AI insights

• Automate enterprise business processes

Because AI applications access current operational information instead of outdated copies, organizations can improve both the accuracy and reliability of AI-generated insights.

Deploying Multi-Agent Workflows with Gemini Enterprise and SAP Joule

Enterprise AI is evolving beyond chatbots and virtual assistants.

Organizations increasingly want AI agents capable of coordinating complex business activities across multiple departments and enterprise systems.

SAP Business Data Cloud Connect for BigQuery supports this evolution through integration with Gemini Enterprise Agent Platform and SAP Joule.

Instead of relying on isolated AI assistants using separate datasets, organizations can orchestrate intelligent agents that operate using the same trusted enterprise information.

For example, a supply chain workflow could include:

• A procurement agent monitoring inventory levels

• A logistics agent evaluating transportation capacity

• A finance agent validating purchasing budgets

• A planning agent recommending replenishment strategies

• A customer service agent communicating operational updates

Because each agent works with the same live enterprise data through the zero-copy architecture, organizations can reduce inconsistencies caused by outdated or duplicated information.

This creates a stronger foundation for agentic AI capable of automating increasingly complex business operations.

Combining SAP Data with Google's Analytics Ecosystem

Another key capability introduced with SAP Business Data Cloud Connect for BigQuery is the ability to enrich SAP business data using Google's broader analytics ecosystem.

Organizations can combine SAP operational information with datasets such as:

• Google Trends

• Google Maps geospatial data

• BigQuery analytical datasets

• Other enterprise and external data sources

For example, retailers can combine SAP sales data with regional search trends to improve demand forecasting, while logistics teams can combine shipment information with Google Maps geospatial data to optimize transportation planning.

According to Google Cloud, organizations can then publish this enriched data back into SAP Business Data Cloud, allowing downstream SAP applications to benefit from expanded business context without creating duplicate datasets.

This bidirectional data exchange helps organizations create richer analytics while preserving governance and operational consistency.

Conversational Analytics for Business Users

SAP Business Data Cloud Connect for BigQuery also expands access to enterprise analytics through natural language interactions.

Instead of relying solely on SQL queries or traditional dashboards, employees can ask business questions using Gemini Enterprise or SAP Joule.

The AI platforms retrieve live information from both SAP Business Data Cloud and Google Cloud, delivering context-aware responses based on current business operations.

This reduces the technical expertise required to access enterprise insights while making analytics more accessible across finance, operations, procurement, manufacturing, and other business functions.

As a result, organizations can accelerate decision-making and improve productivity throughout the enterprise.

Lower Infrastructure Costs with Zero-Copy Architecture

Beyond accelerating AI and analytics, SAP Business Data Cloud Connect for BigQuery is designed to simplify enterprise data management while reducing operational costs.

Traditional data platforms often require organizations to maintain multiple copies of the same datasets across different environments. Every replicated dataset increases storage requirements, infrastructure management, synchronization workloads, and governance responsibilities.

With its zero-copy architecture, SAP Business Data Cloud Connect for BigQuery enables organizations to query data directly where it resides, eliminating the need to create and maintain duplicate copies.

According to Google Cloud, this approach helps organizations:

• Reduce storage and infrastructure costs

• Minimize ETL pipeline maintenance

• Eliminate data-sharing fees associated with replicated datasets

• Simplify governance and compliance

• Create a more predictable total cost of ownership (TCO)

Instead of investing in additional storage and maintaining multiple copies of enterprise data, organizations can focus on extracting greater value from live business information while keeping it secure and up to date.

Early Customers Are Already Seeing Benefits

Organizations that participated in the preview program are already using SAP Business Data Cloud Connect for BigQuery to address complex operational challenges.

According to Google Cloud, early adopters are using the zero-copy architecture to:

• Break down enterprise data silos

• Accelerate AI and analytics initiatives

• Improve supply chain visibility

• Respond faster to changing customer demand

• Build production-ready AI prototypes more quickly

Because teams can interact directly with live SAP and Google Cloud data, they spend less time building integration pipelines and more time delivering measurable business outcomes.

ElringKlinger Uses Zero-Copy Data for Manufacturing Analytics

Global automotive supplier ElringKlinger is among the organizations evaluating SAP Business Data Cloud Connect for BigQuery.

The company manages complex manufacturing and supply chain operations across multiple countries while relying heavily on SAP BW/4HANA as its reporting backbone.

By using BigQuery as an analytical layer on top of its existing SAP environment, ElringKlinger can analyze live ERP data without migrating or replicating existing datasets.

According to the company, this approach simplifies its data architecture while enabling AI-powered conversational analytics, localized inventory reporting, and future agentic AI use cases for global supply chain management.

The implementation also allows ElringKlinger to preserve its existing SAP investments while expanding enterprise analytics and AI capabilities.

Partners Are Building Enterprise AI Solutions

SAP and Google Cloud's global partner ecosystem is already developing industry-specific use cases with SAP Business Data Cloud Connect for BigQuery.

Rather than treating AI as isolated experiments, partners are combining trusted SAP business data with Google's analytics and AI services to help organizations deploy intelligent agents that automate complex business operations while maintaining governance.

Industry partners highlighted several practical applications of the integration:

• Accenture sees the platform as a foundation for scaling agentic AI by combining trusted financial, operational, and sustainability data with Gemini Enterprise to build intelligent agents and modernize enterprise operations.

• Deloitte demonstrated how an autonomous procurement agent could simultaneously analyze live SAP inventory data and market information in BigQuery to automatically reroute supplier orders during disruptions, helping reduce operational downtime.

• KPMG believes the integration provides a scalable foundation for modern enterprise planning, analytics, and future AI workloads, while emphasizing that successful adoption depends on implementation strategy, data quality, and organizational readiness.

• PwC is helping organizations combine SAP and non-SAP enterprise data inside Google Cloud to create a trusted foundation for AI-powered analytics, governance, compliance, and intelligent business workflows.

Together, these examples demonstrate how zero-copy enterprise data architectures are enabling organizations to move beyond proof-of-concept AI projects toward production-ready business automation.

Powering the Next Generation of Agentic AI

According to Google Cloud, enterprise AI requires more than simply connecting large language models to enterprise databases.

AI agents need access to trusted business context, semantic metadata, and current operational information to execute complex business processes accurately.

SAP Business Data Cloud Connect for BigQuery addresses this challenge by securely sharing both enterprise data and business semantics across SAP Business Data Cloud and Google Cloud.

Rather than working with isolated database records, AI agents can understand relationships between suppliers, inventory, financial transactions, manufacturing operations, and other business entities.

This richer understanding helps support intelligent automation across finance, procurement, manufacturing, supply chain management, and other enterprise operations.

Regional Availability

Google Cloud confirmed the following availability for the platform:

SAP Business Data Cloud is currently available in Google Cloud regions including:

• Australia (Sydney)

• Brazil (São Paulo)

• Germany (Frankfurt)

• India (Mumbai)

• Israel (Tel Aviv)

• Japan (Osaka)

• Saudi Arabia (Dammam)

• United States (Iowa)

SAP Business Data Cloud Connect for BigQuery is now generally available globally for all Google Cloud customers.

The integration currently supports SAP Business Data Cloud deployments hosted on:

• Google Cloud

• Amazon Web Services (AWS)

Support for SAP Business Data Cloud deployments hosted on Microsoft Azure is planned for a future release.

Conclusion

The general availability of SAP Business Data Cloud Connect for BigQuery marks another milestone in the long-standing partnership between SAP and Google Cloud.

By introducing secure, bidirectional zero-copy access between SAP Business Data Cloud and BigQuery, the integration enables organizations to use live enterprise data for analytics, AI, and intelligent automation without the cost and complexity of traditional data replication.

Beyond simplifying data access, the platform preserves business semantics, metadata, and governance while connecting SAP Business Data Cloud, BigQuery, Knowledge Catalog, Gemini Enterprise, and SAP Joule into a unified enterprise AI ecosystem. Organizations can enrich SAP data with Google Cloud datasets, publish enriched information back into SAP Business Data Cloud, and build conversational analytics and multi-agent workflows using trusted, real-time business data.

As enterprises continue moving from AI experimentation to production deployments, success will increasingly depend on providing AI systems with governed, semantically rich, and current business information rather than isolated data copies. SAP Business Data Cloud Connect for BigQuery provides organizations with a practical foundation for enterprise analytics, intelligent automation, and the next generation of agentic AI.