I want to understand how Quicksight uses ML based anomaly feature behind the scenes and more specifically once it finds anomalies, how does Quicksight do contribution analysis to find the key contributors?

Hello @Mehroz , I’ll link some documentation here. Let me know if there is anything else I can do to assist! Gaining insights with machine learning (ML) in Amazon Quick Sight - Amazon... How to use Amazon Quick Sight and AWS machine learning to help you make data-driven decisions. …

Hello @Mehroz , welcome to the Quick Sight Community! Honestly, a lot of these things are going to depend on what data you are analyzing in Quick Sight, whether you are collecting data that displays a meaningful change over time, and how long you have been collecting it. I would highly recommend loo…

Thanks @WLS-DM , I am trying to replicate the Quicksight ML-based anomaly detection in Sagemaker. The RCF implementation of sagemaker does not provide the explanation like it does in Quicksight. I tried to use Amazon Q for explanation of Key Driver in Quicksight and it told me that Quicksight use re…

Hello @Mehroz , I do feel like I read on a document somewhere the Quick Sight anomaly detection uses regression, but I can’t remember where I saw that. I will see if I can find some other information to send over to you, but asking Amazon Q was a great idea!

How does Quicksight contribution analysis work?

Q&A

WLS-DM February 9, 2024, 5:02pm 5

Hello @Mehroz, I’ll link some documentation here. Let me know if there is anything else I can do to assist!

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How does Quicksight contribution analysis work?

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