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      SAP Business Data Cloud: Modernize your Enterprise Data and AI foundation 

      SAP Business Data Cloud (SAP BDC) is SAP’s managed unified data platform that brings together governed business data, analytics, planning, and AI capabilities in one environment.

      It helps organizations eliminate data silos, strengthen SAP data integration, and establish an AI-ready data foundation for analytics, planning, and intelligent business processes.

      It brings together existing SAP products such as SAP Datasphere, SAP Analytics Cloud (SAC), and SAP HANA Cloud while extending them with data products, intelligent applications, and deeper support for AI-driven use cases, including SAP machine learning and SAP predictive analytics.

      For organizations modernizing SAP data landscapes, it is fast becoming a key reference point for what comes next. 

      Nirmalya Maitra
      Nirmalya Maitra

      Director, Data and Analytics Capability Lead

      KPMG Switzerland

      What is SAP Business Data Cloud and what does it replace? 

      SAP Business Data Cloud is the umbrella platform SAP is building for enterprise data and AI. Rather than treating data warehousing, analytics, planning, and AI as separate layers, BDC brings them together in one managed environment built around SAP business context.

      It includes core services such as SAP Datasphere and SAP Analytics Cloud, while extending them with governed data products, semantic relationships, intelligent applications, and embedded options for more advanced data and AI scenarios.

      Rather than serving as a direct one-for-one replacement for a single tool, it represents a move away from siloed data warehousing, reporting, and planning setups toward a more integrated and managed business data foundation. 

      Organizations running SAP Business Warehouse (SAP BW) or SAP BW/4HANA need a clear path forward. SAP Business Data Cloud provides a framework for modernizing existing data warehouse investments while preparing for future analytics and AI requirements.

      This is particularly relevant for organizations running SAP S/4HANA, where data modernization initiatives increasingly focus on creating a unified foundation for analytics, planning, and AI.

      Differentiation:
      BDC vs. Datasphere vs. Analytics Cloud vs. BW 

      SAP BDC is best understood not as another standalone product alongside SAP Datasphere or SAP Analytics Cloud, but as the broader operating model that brings these capabilities together.

      As organizations modernize analytics, planning, and AI capabilities, understanding how unified data platforms work becomes increasingly important. 

      In that context, SAP Business Data Cloud provides a framework that combines data governance, business context, and AI services within a single operating model.

      For BW customers, that distinction matters because the question of modernization is not only which tool to use, but which platform model will support future analytics and AI needs. 

      Component

      Primary role

      How it relates to BDC

      SAP Business Data Cloud

      Managed platform for governed data, analytics, planning, and AI

      The broader platform construct that brings services and capabilities together

      SAP Datasphere

      Semantic modeling, data integration, and data warehousing

      A foundational component within BDC

      SAP Analytics Cloud

      Analytics, dashboards, planning, and insight consumption

      A core data consumption and reporting and planning layer within BDC

      SAP BW / BW/4HANA

      Legacy and current warehouse foundation for many SAP reporting landscapes

      An installed base that BDC is designed to modernize, extend, or gradually transition away from

      The 2027 deadline:
      Why SAP BW customers must act now 

      The strongest driver behind SAP BW modernization is timing. The end of SAP BW 7.5 mainstream maintenance in December 2027 is a key milestone for many organizations. Organizations that still rely heavily on BW need to define a credible path forward now rather than defer the decision.

      Developing a clear BW migration strategy early helps reduce risk, prioritize investments, and prepare the organization for future analytics and AI requirements.

      The right path depends on landscape complexity, customization, and business requirements. However, the goal is the same: protect today’s reporting backbone while preparing for a more cloud-oriented, AI-ready architecture.

      For many enterprises, that means evaluating SAP BW Private Cloud Edition (PCE), BW/4HANA, or a staged transition toward SAP Datasphere within the broader BDC model. 

      Migration paths: PCE, BW/4HANA, and BDC 

      There is no single migration path that fits every BW customer.

      Some organizations will choose a lift approach into private cloud edition (PCE) to preserve existing assets and gain more time for a bigger transformation.

      Others will move toward SAP BW/4HANA to gain performance efficiencies and initial exposure to BDC capabilities via Data Product generator.

      Finally, SAP BDC will represent a broader architectural shift rather than a technical migration path.

      In this scenario, SAP Datasphere becomes the foundation for modelling, while composable data products, AI integration, and intelligent applications support more advanced planning and reporting scenarios in SAP Analytics Cloud.

      The most effective strategy is usually phased rather than disruptive, combining continuity for critical reporting with targeted modernization where business value is clearest. 

      AI-assisted migration with the BW Migration Assistant 

      AI-assisted migration is becoming an important part of the BW transition conversation.

      The BW Migration Assistant signals SAP’s direction of travel toward faster assessment, pattern recognition, and guided conversion support for existing BW estates, helping organizations speed up their broader BW migration strategy.

      For customers, the value lies less in full automation and more in reducing effort. 

      The tool can support landscape analysis, identify reusable objects, and speed up decisions on what should be lifted, redesigned, or retired.

      Used well, such tooling can help organizations turn migration from a technical backlog item into a more manageable transformation program while identifying opportunities to simplify data models and improve data quality.

      Key BDC capabilities: data products, knowledge graph 

      What gives SAP Business Data Cloud its strategic weight is not only consolidation of existing tools, but the addition of capabilities designed for reuse and intelligence at scale.

      Data products are governed, business-ready assets that can be shared and reused across analytics and AI scenarios.

      This helps create a single source of truth across multiple data sources, making trusted business data more accessible to both business users and data engineers, while helping organizations maintain data quality and governance standards.

      SAP’s business knowledge graph helps preserve business meaning and relationships so that data remains contextual rather than becoming just another technical extract.

      SAP is positioning Joule as a natural-language interaction layer. It complements open data-sharing approaches such as delta sharing and zero-copy patterns, intelligent insight apps, and advanced data engineering and machine-learning capabilities through SAP Databricks. These capabilities also provide a foundation for emerging SAP AI agents that can interact with business data more intelligently and contextually.

      How BDC relates to Snowflake and Databricks 

      BDC should not be viewed as an attempt to recreate every capability of independent lakehouse or data cloud platforms inside SAP’s own stack.

      Rather, SAP is positioning it as a business-data-centric foundation that incorporates the SAP-delivered SAP Databricks and SAP Snowflake options available within the BDC model, while preserving SAP semantics, governance, and process context across SAP landscapes, including SAP Business Suite and SAP S/4HANA environments.

      For SAP-centric enterprises, BDC may serve as the semantic and governed data layer. It provides a single source of truth.

      Partner platforms can extend analytics, AI, collaboration, and broader ecosystem reach for organizations integrating data across SAP and non-SAP environments.

      BDC for Swiss industries:
      Pharma, Manufacturing, and Banking 

      In Switzerland, the relevance of SAP Business Data Cloud is especially strong in industries where regulated processes, complex operations, and high-value data intersect.

      In pharma, the priority is often governed access to trusted data across quality, supply, and compliance processes.

      In manufacturing, the focus tends to be on connecting operational and real-time data, planning, and analytics more tightly while modernizing long-standing BW landscapes.

      In banking, the attraction lies in combining stronger governance with a more flexible foundation for analytics and AI, particularly where institutions want to reduce complexity without losing control of data lineage and business meaning across SAP ERP and analytics environments. 

      Across these industries, the common challenge is balancing innovation with governance. Organizations want to make trusted data more accessible while maintaining security, compliance, and transparency.

      As AI adoption accelerates, many enterprises are also looking for ways to connect analytics, planning, and operational data within a consistent framework.

      In this context, SAP Business Data Cloud can help establish a governed foundation that supports both business users and technical teams while enabling more effective use of data across analytics and AI initiatives.

      For Swiss enterprises facing both modernization pressure and regulatory expectations, BDC offers a timely platform discussion rather than a purely technical product decision.

      How KPMG helps you implement SAP BDC 

      KPMG helps organizations define their BW migration strategy, design a scalable SAP data architecture, and accelerate SAP BDC implementation.

      Our teams support the transition from SAP BW and SAP BW/4HANA environments to future-ready business data platforms.

      We help clients unlock value from analytics, AI, and SAP Business Data Cloud capabilities. We also provide SAP Analytics Cloud consulting to help organizations create a trusted foundation for reporting, planning, and decision-making.

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      Meet our expert

      Nirmalya Maitra
      Nirmalya Maitra

      Director, Data and Analytics Capability Lead

      KPMG Switzerland

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