Hi @brekrut , thanks for your reply. Source is set to update its incremental date field to latest date everyday. It was as per client's requirement. Client did not want to loose on old data or users who are inactive for few months (as TTL is applied). New data gets generated everyday and historical ...

Hi @_Manoj_Kumar_ , thanks for your reply. I also confirmed with Adobe support, they said duplicate data will indeed affect model predictions. And currently there is no de-dupe logic as use cases might varry for different businesses. Thanks

Hi all,  @_Manoj_Kumar_ @nnakirikanti @dhanesh04s @an1989 @renatoz28 @brekrut @ccg1706 @somen-sarkar @saswataghosh @NickMannion  I was wondering if customer AI instance expires after outcome period or it goes on until its manually disabled? For example, if model/customer AI instance is created to pr...

Thanks @akshaykapil23 , for your reply. Now my understanding is clear

Hi @_Manoj_Kumar_ , Thanks for your reply.  For the use case, there were more than one product code which were mapped to a product group. So a certain product code could have more than one product group mapped to it. In that case, I was not sure how the mapping would happen to a profile. Incase of c...

Thanks @Parvesh_Parmar , I had asked the same to Adobe.. this is what I got as reply - "Customer AI analyzes the datasets, the event TTL is applied on the profile store" Will try to check with them how Pseudonymous data expiration works at data lake level. Thanks,Sambit Sahu

In customer AI historical data requirements, its mentioned that data required = Eligible lookback window + outcome window. Where the eligible lookback window is defined in the eligible population.  So, if I set eligible population to be something like - web activity in last 60 days and set goal cond...

I am using a event type dataset for customer AI instance which has a daily data ingest frequency and hence contains duplicate rows of data with latest timestamp. So, will the duplicate records affect my model predictions?  (Judging from the influential factors, I do think the results might be influe...

Hi @Parvesh_Parmar , Thank you so much for your quick response. Please correct me if I am wrong, I had the understanding that TTL only impacts the profile store and it does not affect the data stored in the datalake. Only I guess, the pseudonymous profile data would get expired from both profile sto...

From the AEP Architecture diagram I think Customer AI works at datalake level but not at profile store level, so I think TTL set on an events type dataset will not affect customer AI data requirements. Please let me know if my understanding is correct.  Thanks