What limits the structure of a hierarchy in a dimension table?

What limits the structure of a hierarchy in a dimension table?

• A. Number of attributes included.
• B. Number of relationships shown among groups.
• C. There is a limit to the number of levels.
• D. None of the above.

Answer: (C)

In a dimension table, the structure of a hierarchy is limited primarily by the number of levels that can be included. This is because hierarchies are designed to organize data in a multi-level format, often representing different degrees of granularity. For instance, a typical geographic hierarchy might contain levels such as country, state, city, and postal code. Each level in the hierarchy provides a means to drill down or roll up the data for analysis, so defining a clear limit on the number of levels helps ensure that the hierarchy remains manageable and comprehensible. When there are too many levels in a hierarchy, it can lead to confusion and complexity, making it harder for users to navigate the data and draw insights. Therefore, setting a limit on the number of levels helps maintain clarity and usability within the dimension structure, ensuring that end-users can efficiently analyze the data without being overwhelmed by excessive granularities.

In a dimension table, the structure of a hierarchy is limited primarily by the number of levels that can be included. This is because hierarchies are designed to organize data in a multi-level format, often representing different degrees of granularity. For instance, a typical geographic hierarchy might contain levels such as country, state, city, and postal code. Each level in the hierarchy provides a means to drill down or roll up the data for analysis, so defining a clear limit on the number of levels helps ensure that the hierarchy remains manageable and comprehensible.

When there are too many levels in a hierarchy, it can lead to confusion and complexity, making it harder for users to navigate the data and draw insights. Therefore, setting a limit on the number of levels helps maintain clarity and usability within the dimension structure, ensuring that end-users can efficiently analyze the data without being overwhelmed by excessive granularities.