International PIKON Blog

Modernizing SAP BI: Why traditional architectures no longer work

Dušan Dokić
September 30, 2025
20 Minutes

Which SAP Business Intelligence tools are (soon) no longer up to date?

Within the SAP portfolio, there are established BI tools that have been in use across companies for many years. However, some of them are reaching their limits when it comes to flexibility, self-service capabilities, and future readiness. In particular, SAP BusinessObjects and the classic SAP Business Warehouse (BW) are now considered outdated — or are on the verge of becoming so.

SAP BusinessObjects

SAP BusinessObjects (SAP BO) is an on-premise BI suite for professional reporting, particularly known for tools such as Web Intelligence (WebI), Crystal Reports, and the Universe model. For many years, BusinessObjects was the standard solution for highly precise, pixel-perfect reporting in companies.

Advantages
SAP BO provides stable enterprise reporting and enables complex, formatted reports, especially in finance and production. Companies value its reliability, maturity, and deep integration with SAP systems.

Disadvantages
From a technology perspective, SAP BO is now outdated. It lacks cloud capabilities and modern self-service options. Changes usually require extensive IT projects. Maintenance for older versions will soon end (version 4.3: mainstream support until 2025, extended support until 2027). The planned successor version from 2025 will be functionally reduced and brings no major innovations. Modern visualizations and dashboards are largely missing.

Expert assessment
SAP positions the SAP Analytics Cloud (SAC) as the strategic successor. Companies should consider an early transition to SAC or explore hybrid scenarios. While SAP BO still offers investment protection until after 2030, in the long term a shift to modern tools is strongly recommended.

SAP Business Warehouse

SAP Business Warehouse (SAP BW) is SAP’s classic data warehouse solution for consolidating SAP and non-SAP data. For decades, BW served as the central data repository in many companies — first on a NetWeaver basis, later on HANA.

Advantages
SAP BW is valued for its deep integration into SAP systems, its extensive predefined content (Business Content), robust data governance, and reliable historization. In combination with HANA, it also enables high-performance analytics and complex data transformations.

Disadvantages
At the same time, the classic BW 7.x on NetWeaver is now outdated. The modeling is complex and inflexible, adjustments are time-consuming and require specialized expertise. Self-service functions are largely missing, which means that business users often rely on IT or fall back on Excel. Even BW 7.5 on HANA is still based on legacy concepts and does not fully exploit modern technologies. In addition, mainstream support for BW 7.5 will end in 2027, and extended support in 2030. Innovation has effectively come to a halt for several years.

Expert assessment
Since 2016, SAP has positioned SAP BW/4HANA as the official successor, with long-term support guaranteed until at least 2040. Analysts point out that pure on-premise solutions are losing relevance. Requirements such as cloud integration, self-service, and agility can hardly be achieved with BW 7.x. Companies should therefore rethink their BI strategy at an early stage and move towards modern platforms like SAP Datasphere or hybrid architectures.

Conclusion
SAP BusinessObjects and the classic SAP BW were reliable tools for many years, but they are now technologically outdated and hinder flexibility. The future clearly lies in modern SAP solutions — particularly in cloud-based or at least HANA-based platforms.

Which SAP Business Intelligence tools are future-proof?

SAP BW/4HANA

SAP BW/4HANA is the successor generation of the classic BW, developed for the in-memory platform SAP HANA. Introduced in 2016, it is not merely an upgrade but an independent product with a modernized architecture and simplified handling.

Advantages
As a state-of-the-art data warehouse solution, BW/4HANA can analyze massive volumes of data in real time—regardless of whether the sources are SAP or non-SAP, on-premise or cloud, structured or unstructured. Thanks to SAP HANA, queries run dramatically faster compared to previous BW versions. SAP has also simplified data modeling significantly: the new Data Flow Modeler offers a graphical interface that improves usability. Overall, the architecture has been streamlined, with many obsolete object types from BW 7.x removed. Extensive self-service functionality is available, enabling business departments to build their own analyses without always depending on IT for new data models. BW/4HANA also integrates seamlessly with SAP S/4HANA (operational reporting) and can include live data directly from S/4. Another advantage is the long support horizon: SAP guarantees maintenance at least until 2040, providing strong investment security. For companies that cannot or do not want to fully move to the cloud in the medium term, BW/4HANA represents a solid, future-ready data warehouse anchor.

Disadvantages
Despite its modernization, BW/4HANA remains a complex enterprise solution that requires significant expertise. Migrating from older BW versions is often labor-intensive, which discourages many companies. In addition, SAP’s innovation focus has clearly shifted towards cloud solutions such as SAP Datasphere, meaning that BW/4HANA will increasingly be used primarily in hybrid scenarios. Flexible self-service architectures and integrated frontend tools are also still largely missing.

Expert assessment
BW/4HANA is considered a solid interim solution for customers who are not yet ready or willing to fully move to the cloud. However, experts advise against viewing BW/4HANA in isolation. Instead, it should be combined with complementary cloud tools such as SAP Datasphere and SAP Analytics Cloud (SAC). Rather than simply migrating, companies should proactively evaluate new tools and develop a future-oriented BI strategy to avoid ending up stuck in another rigid architecture.

SAP Analytics Cloud

The SAP Analytics Cloud is SAP’s leading analytics and planning tool in the cloud. First developed in 2015 under the name Cloud for Analytics, SAC combines business intelligence, planning, and predictive analytics in a single integrated software-as-a-service (SaaS) solution. It runs entirely on the SAP Business Technology Platform (BTP) and is accessed through a browser frontend. With SAC, users can build dashboards, visualize reports, perform ad-hoc analyses, and even carry out planning functions such as budgeting and forecasting — all within one unified environment.

Advantages
SAC stands out for its consistent, end-to-end concept: from data connection to visualization, everything happens within one platform. For SAP customers, the live data connection is particularly attractive. SAC can connect in real time with SAP HANA, S/4HANA, SAP BW/4HANA, SAP Datasphere, and even SAP BusinessObjects Universes. This means existing data sources can be integrated without replication, and up-to-date information is available immediately within the SAC dashboard.

At the same time, non-SAP data — such as from SQL databases or cloud services — can also be integrated. SAP continues to expand this capability, especially through its close integration with SAP Datasphere. SAC is user-friendly, with a modern HTML5 interface and drag-and-drop functionality. Self-service BI is a core principle: business users can create their own stories (dashboards), filter, and drill down, reducing their dependency on IT for evaluations. In addition, SAC offers preconfigured business content libraries for various SAP applications, making it easier to get started. From a CFO’s perspective, the ability to seamlessly move from actuals to planning (including what-if simulations), all version-controlled in the cloud, is a major advantage. Finally, as a cloud service, SAC is always up to date — with quarterly updates delivered directly by SAP — which relieves the internal IT department from infrastructure maintenance.

Disadvantages
Despite these strengths, there are also limitations. Live connections require high-performing networks and sometimes additional setups. Large data volumes can impact performance, often making data imports necessary. Some specialized functions were initially missing, though SAP has gradually added them over time. The per-user licensing model can also become costly for organizations with large user bases.

Expert assessment
SAP clearly positions SAC as its strategic BI platform for the future. This is also reflected in independent evaluations: in the Gartner Magic Quadrant for Analytics & BI, SAP (with SAC as its flagship product) is ranked as a Visionary. The strategy of unifying BI, planning, and predictive analytics in a cloud solution is widely regarded as modern and future-proof. Experts particularly emphasize SAC’s high level of integration within the SAP ecosystem. With the connection to SAP Datasphere, SAP is taking SAC to the next level by enabling semantic data models and real-time data from a wide variety of sources.

SAP Datasphere

SAP Datasphere is SAP’s next-generation cloud data management and data warehouse solution. It was first introduced in 2019 as SAP Data Warehouse Cloud (DWC) and rebranded in 2023 as Datasphere with extended functionality. Datasphere forms a central part of SAP’s Data-to-Value portfolio, together with SAP HANA Cloud, SAP Analytics Cloud (SAC), and SAP Data Intelligence Cloud. At its core, Datasphere is a SaaS platform that enables companies to integrate, model, and prepare data from various sources for analytics, with a particular focus on self-service data warehousing. Technically, it runs on SAP HANA Cloud, enhanced with a data virtualization layer and new modeling tools such as the Data Builder and Business Builder.

Advantages
SAP Datasphere combines the strengths of a traditional data warehouse — consistency, governance, and centralized data models — with the flexibility of modern self-service approaches. A key benefit is the integration of both cloud and on-premise data sources. Prebuilt connectors allow companies to link not only to SAP systems (such as S/4HANA or BW/4HANA) but also to SQL databases and even file-based data. The Data Flow component enables ETL processes to extract, transform, and persist data in the cloud, while virtualization allows direct access to less frequently used data without full replication, which supports hybrid scenarios.

Datasphere provides two modeling environments: the Data Builder for technical data flows and the Business Builder for the semantic modeling of business entities. This dual approach fosters collaboration between IT and business departments: IT can ensure governance and data quality through central models, while business users can make refinements or combine data for their own purposes. Properly implemented, this setup significantly increases agility, giving end users a “data shopping” experience where validated, reusable data models are available in an easy-to-use format.

Another major strength is its seamless integration with SAC: live connections between Datasphere and SAC can be established in just a few clicks, allowing models from Datasphere to be directly consumed in SAC. The platform is also open to third-party tools such as Tableau or Power BI via JDBC or OData. As a cloud service, Datasphere benefits from automatic updates, scalable infrastructure, and usage-based pricing. Moreover, its growing partner network and integrations with platforms like Databricks allow companies to combine SAP data with AI and machine learning scenarios. By supporting widely used languages such as SQL and Python, Datasphere also lowers the barrier for non-SAP developers, making the platform accessible to a broader user base.

Disadvantages
Despite its rapid development, Datasphere is still a relatively young product. Some functions that were standard in classic BW were only gradually added, and the hybrid approach requires companies to rethink governance and responsibilities. Best practices for architecture are still evolving, meaning organizations must find their own way step by step. For highly detailed real-time analyses, on-premise systems can still have advantages. Licensing also requires careful calculation, and the long-term future of the BW Bridge — SAP’s transition solution — remains uncertain. Overall, however, these challenges are seen as temporary, as SAP is pushing the platform’s development forward at a rapid pace.

Expert assessment
SAP Datasphere plays a key role in SAP’s BI strategy. In combination with SAC, it forms an end-to-end platform that tightly integrates data management and analytics, offering users a consistent experience. The openness of the solution is especially noteworthy: through its expanding partner network and integrations with providers like Databricks, SAP data can now be seamlessly combined with big data and AI scenarios. This sets SAP apart from competitors and opens new opportunities for data-driven innovation. Datasphere is therefore considered a future-oriented bridge between proven SAP data management and modern cloud technology. At the same time, it offers investment protection for existing customers, as classic BW systems can continue to run until 2030 and be migrated gradually. Experts recommend that companies start engaging with Datasphere today and launch pilot projects early on to gain experience and actively shape the transition.

SAP Business Data Cloud (BDC)

SAP Business Data Cloud (BDC) is SAP’s newest strategic product in the Data & Analytics space. Officially launched in February 2025, it is a fully managed SaaS solution designed to unify all SAP data and seamlessly integrate third-party data. BDC can be seen as a “roof” over the previously mentioned tools: it combines the technologies of SAP Datasphere and SAP Analytics Cloud with integrated Databricks functionality. SAP describes it as a unified semantic layer for both SAP and non-SAP data. Following the concept of a business data fabric, the BDC aims to make all mission-critical enterprise data accessible in its business context, serving as the foundation for both analytics and AI. In practice, it includes analytics functions (SAC), data management (Datasphere), as well as prebuilt data products and AI services.

Advantages
The vision behind the BDC brings several key benefits. First, it eliminates data silos: all relevant enterprise data, whether from SAP transactional systems or external sources, can be connected within an open ecosystem. Through the common semantic layer, all data “speaks the same language,” enabling consistent real-time analytics. SAP compares the BDC to a “highly skilled translation engine” for different data languages.

Second, the BDC is fully managed by SAP. Unlike Datasphere, where customers still had to set up and configure spaces themselves, SAP now takes care of the setup and operation of the entire environment. Functions such as Databricks integration are embedded out of the box. As Michael Ameling, Head of Product at SAP, puts it: “SAP puts everything together and takes care of management – one contract, one pricing model.” This one-stop principle drastically reduces the customer’s operational workload.

Third, the BDC includes built-in AI support. With the SAP Knowledge Graph as the foundation for semantic modeling and tools such as the Joule AI Agent Builder, BDC enables trustworthy AI on enterprise data. Preconfigured Insight Apps are also provided — analytical applications for specific business processes (such as Working Capital Insights) that are ready to use and designed to deliver faster business insights.

Fourth, BDC has been designed as a multi-cloud, modern architecture. Companies can simplify their data landscapes while harmonizing data from various environments. The close partnership with Databricks is seen as a competitive advantage: recognizing that many customers already rely on Databricks, SAP combines its transactional data strengths with Databricks’ ML and AI capabilities. This “best-of-both-worlds” approach (SAP + open data ecosystem) sets SAP apart from other providers. Importantly, the BDC also enables a smooth transition for existing customers. For example, those still running BW on HANA can continue to use it until 2030 while gradually transferring their data into the BDC as “data products.” This combination of investment protection and cutting-edge technology is a significant benefit.

Disadvantages
However, challenges remain. SAP faces strong competition from providers such as Snowflake or Microsoft Azure, which already offer mature solutions. The tight alignment with the SAP ecosystem may be restrictive for companies with highly heterogeneous IT landscapes. Migration requires effort, as existing data models, processes, and logic need to be adapted. For IT teams used to a high degree of autonomy, the managed-service model also means less direct control over individual components.

Expert assessment
From an expert perspective, the announcement of the SAP Business Data Cloud marks a decisive step forward in SAP’s data strategy. BDC unites processes, data, and AI in an integrated end-to-end cloud suite, extending SAP’s traditional strengths — especially end-to-end business process chains — consistently into the cloud. It is regarded as a second central pillar alongside SAP’s cloud business suite, since it consolidates data into a unified semantic layer that provides the foundation for analytics and AI. The partnership with Databricks further differentiates BDC from competitors, enabling companies to combine SAP business data with scalable big data and AI capabilities for the first time.

The potential is enormous, even if actual market adoption will become clearer over the coming years. For existing customers, BDC is emerging as the strategic path forward. Leading enterprises such as Henkel already highlight the added value, noting that the Business Data Cloud bridges the gap between technology and decision-making by delivering harmonized, context-rich data as a basis for AI and analytics. In summary, the BDC can be seen as a true game changer that future-proofs SAP’s BI and data landscape — provided that SAP consistently executes on its ambitious strategy.

When is the right time to move to modern SAP BI tools?

Given the above, the key question is: how do you know when your BI architecture needs to be modernized? Here are some typical challenges and warning signs that indicate the time for change has come:

End-of-life or lack of further development: Is your BI platform running out of support in the near future, or is the vendor no longer delivering innovations? An example is SAP BusinessObjects BI 4.2 or BW 7.x, both of which will reach end of support in 2027. If your core BI tool is heading for retirement, you should proactively plan the migration before the pressure of a support deadline becomes critical.
Rigid architectures block requirements: Do even small changes to reports or data models require extensive IT projects? Do you need workarounds because the system is inflexible (for example, reprocessing mass data in Excel)? Such rigidity is a clear signal that more modern, agile tools are needed. In many legacy systems, each new data source or KPI becomes a mini-project. Modern BI platforms drastically reduce this effort.
High manual effort and Excel dependency: Are reports exported from the BI system and then manually reworked in Excel because the system cannot provide certain evaluations? That was the case at Stadtwerke München, until SAC was introduced and “old reports and Excel” could finally be replaced. A BI environment that drives users into “Excel exile” is no longer fit for purpose.
Lack of self-service capability: If business departments must rely on IT for every new analysis and cannot create their own dashboards, responsiveness suffers. Modern BI strategies emphasize empowering business users, with governance in place. If this element is missing, user frustration increases — a clear modernization indicator.
Difficult integration of new data sources: Are more and more cloud services or external data sources entering the picture that your old BI system cannot easily integrate? Examples include IoT data, web analytics, or third-party cloud data. If integration “hacks” or detours are necessary, a more flexible data platform is required. The trend is clearly moving toward integrated data landscapes, as emphasized by DSAG. A warning sign is when BI and the data warehouse are isolated and unable to keep pace with digital transformation.
Performance and scalability problems: Do reports take too long, or can your current tools no longer cope with growing data volumes (big data)? In-memory technologies and cloud data lakes provide relief here. Do not wait to make the switch if response times and data volumes are becoming a business risk.
High maintenance costs for legacy systems: Legacy BI — especially custom developments or heavily modified systems — often causes disproportionately high operating and maintenance costs. In contrast, modern cloud solutions deliver with SaaS operations and automatic updates. A cost-benefit analysis often shows that a switch is more economical in the medium term, also because staff resources are freed up for value-adding activities.
Vendor strategy shift: Is your BI provider focusing on a completely new technology? If so, you should follow. SAP, for example, is clearly pushing cloud solutions and data products (see BDC). SAC is explicitly communicated as strategic, while BusinessObjects is only “kept alive.” Do not bet on the wrong horse.

In summary, the right time to modernize is at the latest when you recognize one or more of these signals. Do not wait until urgent pressure arises, such as the end of support in 2027. BI migrations require time — for planning, implementation, and parallel operations. Starting early allows you to modernize step by step, minimize risks, and already achieve quick wins, for example by piloting a self-service tool in one department or launching a new dashboard in SAC.

Of course, the timing depends on each company’s specific situation. A CFO will weigh the effort and costs of a BI transformation project against its benefits and risks. However, the challenges outlined above typically intensify over time: data volumes and variety grow, users demand more real-time capabilities and self-service, and competition does not stand still. Continuing with outdated systems can quickly become a strategic disadvantage, while modern BI architectures act as enablers for data-driven decision-making.

Conclusion

Rigid legacy systems have no place in today’s dynamic business world. Companies that continue to rely on outdated BI architectures risk competitive disadvantages — whether through slow responsiveness, higher operating costs, or untapped data potential. The good news: the SAP ecosystem offers a range of modern tools — BW/4HANA, SAC, Datasphere, and the Business Data Cloud — to make BI landscapes future-proof. The key is not to focus on a single aspect, but to pursue a holistic data strategy. In many cases, it is the combination of the right tools that delivers the best results.

For CIOs and CFOs, this means one thing: act now. Do not wait until your legacy systems reach end of support or your business departments resort to shadow IT out of frustration. Start planning the transition early. This includes analyzing the current landscape, creating a roadmap (possibly with phased transitions), and engaging all stakeholders internally. The challenges — such as migration effort or change management — are real but manageable. Many companies have already made the move (see success stories above) and report afterwards that the benefits far outweigh the effort.

Expert recommendation: Use the transition period until 2027/2030 wisely. Pilot new tools in small projects, train employees in SAC and related solutions, and build internal know-how. This reduces the fear of a “big bang” approach. Hybrid strategies — for example, running BW/4HANA and Datasphere in parallel, or gradually replacing BusinessObjects with SAC — can make the transition smoother. But do not lose sight of the ultimate goal: a BI architecture that is flexible, scalable, and business-oriented.

In conclusion, modern SAP BI tools offer the opportunity to transform BI from a cost center into a strategic success factor. With real-time data, self-service analytics, and integrated AI, companies can make faster and more informed decisions. The technologies are mature — now is the time to use them. Or, in the words of one SAP expert: “Companies should waste no time in setting the course for the future of reporting, analytics, and planning.” With this in mind: take the step toward modernization and lead your SAP BI into a successful future!

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