Calculated dimensions rely on which of the following to function effectively?

Calculated dimensions are a powerful feature that allows users to derive new dimensions based on existing metrics and dimensions in their dataset. The effectiveness of calculated dimensions largely depends on the quality and reliability of the underlying data. Data integrity refers to the accuracy and consistency of data throughout its lifecycle, while source reliability pertains to the trustworthiness of the data sources from which this information is derived.

For calculated dimensions to produce meaningful and accurate results, the data they rely on must be both complete and trustworthy. If the data lacks integrity or comes from unreliable sources, any calculations or analyses that depend on it could yield misleading conclusions, impacting decision-making and strategic planning.

While metrics, historical analysis, and user engagement might play roles in broader analytics practices, they do not directly pertain to the core functionality of calculated dimensions in the same way that sound data integrity and reliable sources do. To generate valuable insights, ensuring that the foundational data is robust and dependable is essential.