As SAP analytics leaders look ahead to the end of SAP Business Warehouse (BW) 7.5 mainstream maintenance in 2027, with extended support available through 2030, a familiar question is resurfacing: how to modernize analytics without getting trapped in another generation of legacy architecture.
Organizations are under pressure to support cloud scale, advanced analytics and AI use cases, while still protecting years of embedded business logic and reporting. The result is a very pragmatic debate; not about what is theoretically possible, but about what is realistic given timelines, budgets and internal skills.
Below are the primary paths analytics leaders are actively weighing in 2026, and the trade-offs that matter most.
Option 1: Stay on SAP BW 7.5 via Private Cloud Edition
For stability with minimal disruption, lifting an existing SAP BW 7.5 environment into a managed private cloud edition can extend the runway to 2030. Existing models, logic and reports remain largely intact, and operational overhead is reduced through managed services.
This path buys time, but it does not meaningfully advance analytics capabilities. Innovation, scalability and AI readiness remain constrained by legacy architecture.
Option 2: Move to SAP BW/4HANA
Transitioning to SAP BW/4HANA offers a longer support horizon and performance improvements through HANA. Modeling is simplified, and some organizations view this as a logical next step after BW 7.5.
However, BW/4HANA PCE is still a database warehouse-centric approach with the added ability to mirror data to an SAP Datasphere object store (data lake). While it modernizes the foundation (compared to SAP BW 7.5), it can still limit cloud-native scaling, cost more than most modern cloud platforms, limit deeper AI integration and broader data product strategies. For many, it feels like a better version of the past rather than a platform designed for what comes next.
Option 3: Replatform to SAP Business Data Cloud with custom data products
A growing number of organizations are considering a full replatforming to SAP Business Data Cloud using a greenfield approach. In this model, data is sourced directly from SAP and non-SAP systems, modeled in SAP Datasphere and delivered through purpose-built Protiviti custom data products.
This approach eliminates BW entirely. It requires upfront redesign of data models and processes, but it enables cloud-native architecture, modern analytics and AI-driven use cases. When paired with Protiviti accelerators, AI development agents focused on automation and semantic enrichment, organizations can reduce manual upfront effort, cost and improve delivery speed.
The key consideration is readiness for change. This is not a lift-and-shift but a strategic reset.
Option 4: Replatform to SAP Business Data Cloud using SAP-managed data products
Some organizations are leaning on SAP-managed data products as the foundation for Business Data Cloud adoption. This can accelerate time to value, particularly for S/4HANA RISE customers, and supports integration with advanced analytics platforms. SAP has laid out a solid foundation with end-to-end prebuilt content (SAP data products and Intelligent Apps) that can reduce the replatforming cost and ongoing maintenance cost.
The limitation is flexibility. Coverage and access of SAP data products can vary depending on system landscape, and organizations with complex or non-standard requirements may need additional work to close gaps.
Option 5: Move to a non-SAP data lake or lakehouse
Others are opting for a more independent approach, extracting data directly from SAP sources and integrating it into platforms like Snowflake, Databricks, Microsoft Fabric, or BigQuery. This method offers maximum flexibility, robust AI and machine learning capabilities and freedom from SAP-specific limitations.
However, this approach comes with a significant trade-off in terms of effort and licensing. Migration and rebuilding can be substantial, and organizations still need a reliable mechanism to extract and manage SAP data effectively. For instance, extracting S/4HANA data into lakehouse storage requires an SAP BDC license. Alternatively, non-SAP CDC tools like Theobald, Precisely, Boomi, CData, and others, or ODP/CDS-based extraction (where technically permitted), can be used as alternatives.
The overall effort involved in this approach can be 3-4 times more compared to the options outlined above due to the openness of the platforms and the lack of comprehensive prebuilt content. Additionally, organizations will need highly skilled datalake developers and architects with a deep understanding of SAP to effectively build everything from scratch that most SAP platforms provide out of the box. For example, the absence of SAP Business Semantics and lineage can quickly turn the lakehouse into a liability.
What the momentum suggests
Across these options, one theme is consistent. Organizations that want to leave BW behind are favoring true replatforming, either to SAP Business Data Cloud with a native, zero-BW architecture or to a non-SAP lakehouse environment.
Private cloud extensions and incremental upgrades remain viable for risk-averse timelines, but they are widely viewed as temporary measures. Full replatforming requires more upfront investment, yet it is the path most aligned with long-term analytics, AI and data product strategies.
For most organizations, the biggest hurdles are rework effort, organizational change management, preservation of deep business logic, licensing and timeline constraints and access to the right skills. Understanding the right trade-offs is the first step to lasting modernization value.
Protiviti helps organizations evaluate BW exit paths based on business complexity, modernization goals and future analytics needs so leaders can choose the right balance between short‑term stability and long‑term impact.
To learn more about our SAP consulting services, contact us.
