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
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Hello @SahuSa1 ,
Your understanding is mostly correct, but let me provide additional clarity:
Customer AI relies on data stored in the data lake for training its models and making predictions. If datasets in the data lake are managed with expiration policies (TTL), the availability of critical data for Customer AI can be impacted. However, if expiration dates or processing rules are configured properly, data will not be deleted prematurely.
Align Data Retention with Customer AI Requirements:
Understand the Purpose of AEP:
Hope it will help!
Best regards,
Parvesh
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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 store and datalake if it has no activity within the TTL set period, due to its "all or nothing" concept.
(Source - https://www.youtube.com/watch?v=We3RN-41Dik)
So,TTL set on dataset should not affect the data requirements for customer AI right?
Also, can TTL be applied so that data also gets expired from datalake along with profile store?
Please enlighten me.
Thanks,
Sambit Sahu
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