“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.”
In today’s data management landscape, cloud-native platforms like Snowflake, Databricks, AWS, Microsoft Fabric, and SAP Datasphere dominate the presence in many discussions and data strategies. 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.
However, there are many concepts in BW that are functionally strong and beneficial, and over the past decades, they have formed the foundation of numerous large and very large BW platforms for many SAP customers. SAP BW/4HANA addresses challenges that may not have been fully recognized as strengths by its users in the past. Now these strengths are 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 the proven concepts of BW.
Deep Integration of Metadata Management and Business Semantics
SAP BW/4HANA (within its own functionality) offers unparalleled range of metadata, as well as its administration and semantic integration. Info Objects offer extensive semantics, time dependencies, hierarchies, multilingual support and reusability, hiding a table-oriented view in favor of a more object-oriented perspective.
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. In contrast, BW/4HANA’s integrated approach simplifies the management of unified yet complex structured data landscapes.
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, along with standard hierarchy containers and operations for even complex, time-dependent hierarchical structures, further enhances the value of Info Objects.
The handling of slowly changing dimensions and other master data administration tasks is consistent across all master data, both in application and in treatment, which emphasizes one of the long-standing strengths of BW.
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 plays a key role in application lifecycle management, which is deeply integrated into 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 to catalog dependencies. The integrated design of BW/4HANA addresses these challenges natively.
While this list highlights the most important features, it is by no means complete. BW/4HANA offers additional strengths that have made it a robust solution, but these are not listed here. The point is that many of the topics and challenges currently being discussed in relation to the „modern data stack“ were resolved many years ago in BW. For SAP data, a solid BW infrastructure remains a valuable asset that should not be underestimated when considering replacing it merely for the sake of adopting something „new.“
SAP Datasphere: Modernizing BW’s Strengths
SAP Datasphere is now showing clear signs of including some of the conceptual strengths of BW/4HANA features. The following concepts can be found in the more recent releases of SAP Datasphere:
- 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 such as 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
The integrated approach of SAP BW/4HANA 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. Although BW/4HANA is considered a “legacy system,” it will remain relevant for many organizations for years to come. 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.
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