In SAP BW InfoCube design, when is it appropriate to group several characteristics together in the same dimension?

Introduction / Context:
Designing InfoCube dimensions in SAP BW is a key modelling task that has direct consequences for performance and manageability. Characteristics must be grouped into dimensions in a way that keeps dimension tables relatively small compared to the fact table while still supporting required reporting combinations. Certification exams frequently test whether you know that characteristics with one to many or many to one relationships can be grouped effectively, whereas many to many relationships should be avoided in the same dimension.

Given Data / Assumptions:

• An InfoCube consists of a central fact table and several dimension tables.
• Each dimension groups one or more characteristics.
• The size of a dimension table is determined by the number of unique combinations of its characteristics.
• Good design practice aims for relatively small dimension tables compared to the number of fact records.
• We need to know under which relationship pattern characteristics should be placed into the same dimension.

Concept / Approach:
If characteristics have a one to many or many to one relationship, the number of unique combinations between them is limited. For example, each material might belong to one material group, and each material group can have many materials. Putting both characteristics into the same dimension does not explode the number of combinations, because the relationship is hierarchical rather than many to many. By contrast, if two characteristics have a many to many relationship, such as customers and sales promotions, the number of combinations can grow very large, leading to large dimension tables and degraded performance.

Step-by-Step Solution:
Step 1: Recall that the size of a dimension is based on the distinct combinations of all characteristics assigned to it. Step 2: Recognise that characteristics in a one to many or many to one relationship tend to produce fewer combinations, because each value of one characteristic is associated with a limited set of values of the other. Step 3: Understand that many to many relationships can generate a large number of different combinations, which inflates dimension size. Step 4: Review the options and identify that option a describes combining characteristics when they have predominantly one to many or many to one relationships. Step 5: Choose option a as it best reflects the recommended practice in InfoCube dimension design.

Verification / Alternative check:
Consider the characteristics material and material group. Each material belongs to exactly one material group, but each material group can contain many materials. If you place these two characteristics into the same dimension, the number of distinct combinations is roughly equal to the number of materials, which is manageable. Conversely, if you placed customer and sales promotion together, where customers can participate in many promotions and promotions can include many customers, the combinations might multiply rapidly, causing a very large dimension. This simple comparison confirms why one to many or many to one relationships are suitable for common dimensions and why many to many combinations are not.

Why Other Options Are Wrong:
Option b is incorrect because many to many relationships usually result in large dimension tables and should be avoided in a single dimension if possible. Option c is wrong because grouping unrelated characteristics that are never used together is not logical and does not help performance. Option d is misleading because a dimension should never be allowed to reach or exceed the size of the fact table; this is a sign of poor design, not a condition for grouping characteristics. Option e incorrectly suggests that each characteristic needs its own line item dimension, which would defeat the purpose of shared dimensions and is only appropriate for specific scenarios.

Common Pitfalls:
A frequent mistake is to group characteristics simply based on business naming, without analysing their relationships and cardinalities. Another pitfall is to ignore the impact of many to many relationships on dimension size, leading to performance problems after go live. For certification and practical modelling, remember that characteristics with one to many or many to one relationships can safely share a dimension, whereas many to many relationships should be handled with care, often through separate dimensions or different modelling techniques.

Final Answer:
You should group characteristics in the same dimension when they have predominantly one to many or many to one relationships among themselves, so that combining them keeps the dimension table relatively small.