SAP BW/4HANA: The Grey Panther of Data Warehousing

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SAP BW/4HANA: The Grey Panther of Data Warehousing

“And some things that should not have been forgotten were lost. History became legend. Legend became myth. And for twenty years, the BW passed out of all knowledge.”
(Adapted from Galadriel’s famous words)

Cloud-native data management solutions dominate the presence in many discussions and strategies about data management.

Despite its evolution from BW to BW/4HANA and the significant functional improvements it brought, the solution’s 25-year history— evident in many of its functional corners—makes it difficult for BW/4HANA to be perceived as a modern data warehousing solution.

But there are many concepts in BW that are functionally strong and beneficial, and on which in the last decades many foundations of large and very large BW platforms for many customers of SAP were built.

SAP BW/4HANA addresses challenges that, in the past, may not have been fully recognized as strengths by those who used it, but which are now worth remembering in the discussion about the “modern data stack”.

This article revisits some of these strengths in metadata management, governance, orchestration, and automation—highlighting its utility for (classical) well-structured, large-scale EDWs with a focus on SAP systems as the source of data. This short article concludes by exploring how SAP Datasphere inherits and modernizes some of BW’s proven concepts.

Deep Integration of Metadata Management and Business Semantics

SAP BW/4HANA (within its own functionality) offers unparalleled rich metadata, its management and semantic integration. Its Info Objects always provided rich semantics, time-dependencies, hierarchies, multilingual support, and reusability, hiding a table-oriented view in favor of a more object-oriented perspective. Info Objects embed business semantics directly into data models, eliminating the need for external interventions for that purpose. Features like well-defined amount-to-currency relationships and unit conversions are natively extracted from the source in an automated way, ensuring semantic precision throughout the data chain without having to create additional bespoke logic or external tools to enforce system-wide consistency.

In contrast, many modern cloud platforms often depend on third-party tools for advanced metadata management and lineage, particularly in heterogeneous environments with multiple data warehouse solutions. While these tools can offer benefits in multi-platform setups, they also introduce additional licensing costs and integration complexity. By comparison, BW/4HANA’s integrated approach streamlines unified yet complex data landscapes (of structured data).

Master Data Management

BW/4HANA Info objects of type characteristic have always been an excellent support for master data design and management. Info Objects ensure system-wide uniqueness and consistency, managing time-dependent attributes and hierarchies with minimal developer intervention.

Multilingual support for master data and standard hierarchy containers and operations for even complex, time-dependent hierarchical structures further enhance the utility of Info Objects.

Handling slow-changing dimensions and other master data management tasks are homogeneous across all master data in their application and treatment, reflecting one of BW’s long-standing strengths.

Orchestration and Automation with Process Chains

Process Chains in BW/4HANA automate ETL workflows, ensuring tasks are executed in sequence with built-in error handling, scheduling, and logging. In contrast, cloud platforms often rely on external orchestration tools like Apache Airflow or AWS Step Functions, adding tool complexity to data pipeline design and orchestration. BW/4HANA’s native orchestration has proven to simplify large workflows and to reduce maintenance and monitoring overhead. It also has its effects in the application lifecycle management which is deeply integrated in BW.

Logical Scalability and Dependency Management

BW/4HANA’s previously discussed object-oriented approach enables logical scalability and robust dependency management for complex data landscapes. While cloud platforms like Snowflake focus on elastic scalability, managing interrelated data tables often requires additional tools for cataloguing dependencies. BW/4HANA’s integrated design handles these challenges natively.

While this list highlights key features, it is by no means exhaustive. BW/4HANA offers additional strengths that have made it a robust solution, though they are omitted here for brevity. The point here is that plenty of currently discussed topics and challenges in the use of the “modern data stack”[1] have been resolved many years ago in BW and that for SAP data a solid BW infrastructure still is an asset not to be underestimated in its value when it comes to thoughts about substituting it just for doing something “new”.

SAP Datasphere: Modernizing BW’s Strengths

SAP Datasphere is now showing clear signs of including some of the above-mentioned conceptual strengths of BW/4HANA features. We can find the following concepts in the more recent SAP Datasphere releases:

• Multilingual Support: Adapts datasets and reports to user preferences, ensuring global consistency.
• Currency Conversion: Replicates BW’s standardized functionality for seamless ERP-DW integration.
• Time-Dependent Attributes: Maintains historical master data changes with business semantics like “Valid from” and “Valid to”.
• Hierarchies: Incorporates parent-child hierarchies with expanded functionality for modern cloud environments.
• Navigation Attributes: Enables logically easy to understand aggregations of fact data by natural “business objects” without duplicating data, ensuring model flexibility and expressiveness.
• Non-Cumulative Measures: Supports scenarios like stock levels and balances, leveraging delta records for precision.
• BW-Style Measure Types: Includes calculated, restricted, and currency conversion measures, maintaining analytic rigor.
• Variables: Enhances interactivity and flexibility through dynamic parameter settings with a standardized behavior.

Conclusion

SAP BW/4HANA’s integrated approach included solutions for many challenges in metadata management, governance, and scalability, reducing complexity and homogeneous solution patterns in large-scale deployments. While cloud platforms necessitate often third-party tools for similar capabilities, BW/4HANA offers a cohesive solution which his not easily found anywhere else. Despite being labelled as a ‘legacy’ system, BW/4HANA remains and will remain relevant for many organizations for years. Transitioning its proven solutions to a “modern data stack” would require significant effort, discipline, re-skilling and governance, making BW/4HANA a practical choice for the foreseeable future.

SAP Datasphere represents a powerful evolution, blending modern cloud-native architecture with some of the proven concepts of BW/4HANA. It not only supports seamless SAP data integration but also accommodates diverse data sources, offering enterprises a balance of innovation and reliability.

[1] A name which implicitly includes the multi-tool nature of it