I've read some documentation about data management strategy related to process models, but I'm not sure I have understood it. Is it about data available for reporting or something like that? I'm a bit lost...
Could you elaborate a bit more on what you are looking to achieve, or what particular bits and pieces you are referring too?
With regard to processes, your main concerns are what you keep in memory (that's a mostly technical question), what and when you archive (technical as well), and what data you decide to keep within the model (can be a compliance/security consideration, say you have health data). The overall idea is: are you, at some point, possibly need the data within the process model again? If yes, archive. If no, delete. Archive and delete as soon as convenient for your use case.
Hello Marcel, thank you for your answer.
I have no an specific case at this moment, just trying to learn and understand the concept in order to know how to use it in my developments.
From your answer: may I understand that is it all about deciding what and how long you keep available the information collected by the process?
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