Data Modeling Strategies to Avoid Data Inaccuracy and Ensure Consistency

Minimize and eliminate data inconsistency and inaccuracy in SAP NetWeaver BI environments by adopting and adapting the data modeling techniques described here. The author explains the accuracy, benefits, and drawbacks of each.

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Key Concept

Common data modeling approaches produce inconsistent and inaccurate data over time. This results from insufficient understanding of delta processes and different data target behavior, as SAP does not require developers to understand these concepts in detail. An appropriate data modeling technique, such as an intermediate DataStore object with time-independent master data attributes, ensures that information remains consistent and retains appropriate accuracy levels.

Developers must fully understand the nuances of SAP functionality, such as the intricacies of the delta process. Otherwise, SAP NetWeaver BI data models can suffer from data degradation. This can manifest itself in inconsistent or inaccurate data. In some cases, key figures can appear as inappropriately split between characteristics, or as assigned to the wrong characteristics. Data degradation can occur across all versions of SAP NetWeaver BI and with data from any SAP or non-SAP system.

While the inconsistencies and inaccuracies only appear in specific situations and are sometimes limited to a subset of information, they can wreak havoc on user acceptance and confidence in the SAP NetWeaver BI system. Demanding end users rather than specific business requirements often necessitate changing your data modeling strategy.

This article series explains where data problems can appear. Once you’re armed with the tools for understanding the situation, you can avoid the problem in the first place and demonstrate the significance of inaccuracies that unsophisticated data models cause.

In this series, I’ll share common data modeling mistakes and provide appropriate solutions. Correct data modeling requires knowledge of a collection of areas such as time-dependency scenarios, delta updates, different data targets, and transformations (previously update rules in SAP BW 3.x). This article examines how to ensure consistency with the historic time-dependency scenario when using time-independent attributes.