Hi Brenda
1 - This is going to be dependent on the server (how much horsepower it has) - and how large the models/data is. There is some documentation/best practices available that you will want to follow to really utilize the AI Assistant.
2 - Reliable? Hmmm -- Ask google this question "Can I register for the kids Pittsburgh marathon in person the day of the event"
Gemini AI provides an answer of "no". The reality is "yes you can" for I did this last year and "AI provided a No answer to me last year and I was able to register 30minutes before the heat took off". The saying of "garbage in, garbage out" is still true with AI -- maybe worse. In Cognos, if the data is garbage, you will get some bad results returned.
Does it fail? Yea, it can fail and when it does, you will need to do the enriching manually (table by table).
3 - I have not noticed this behavior.
4 - Enriching is time and memory intensive. Other instances on the same server? I guess it comes down to how many instances you are running on each server - horsepower of the server and how much memory is available -- it is memory intensive.
5 - If you make a change to the package which changes the behavior of the data/model, yes you will need to enrich it again.
Here are some links to the documentation regarding the assistant.
https://www.ibm.com/docs/en/cognos-analytics/12.1.x?topic=packages-enriching
https://www.ibm.com/docs/en/cognos-analytics/12.1.x?topic=SSEP7J_12.1.0/com.ibm.swg.ba.cognos.ug_ca_dshb.doc/t_ca_assistant_tips_best_practices.htm
Hope this helps.
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John Cusack
Analytica iQ
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