Calculated fields and parameters in dataset vs analysis

Question & Answer
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1

what is the difference between creating a calculated field and/or parameter in the dataset vs the analysis? are there any performance differences? Is one method superior over the other?

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Hi @huda.h.yazgi
Some points that i would consider while making choice between creating a calculated field and/or parameter in dataset vs analysis:

  1. Changes to calculated fields/parameters in a dataset require refreshing the dataset which can take more time, while changes in an analysis are quicker to test.
  2. Defining them in a dataset allows sharing across multiple analyses, while calculated fields/parameters in an analysis are specific to that analysis.
  3. Moving a calculated field/parameter from an analysis to a dataset protects it from accidental modification.

In terms of performance, calculated fields/parameters defined in an analysis avoid dataset refresh times so may have faster response times when testing changes. However, putting them in a dataset allows leveraging SPICE caching for faster performance once the fields are stable. Overall, this is a design choice. In my opinion, the dataset approach is better when there is a need to share across analyses or when fields are stable, while the analysis approach can be easier for iterative development. The optimal approach depends on the specific use case and needs. Hope this helps.

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