This is an interesting question and I'm really excited that this you're looking into this! AWS has a breadth of data and analytics tools, but it really depends on what your data looks like presently. The page linked above will help narrow down your choices.
If the data needs to be normalized as it's spread across multiple sources, you'd likely need to do some normalization using something like AWS Glue.
Is the data already in a database or csv file and you just want to visualize it using an easy to use interface? Check out Amazon QuickSight. It's our cloud-native, completely serverless BI service and one of my favorites! I'm far from an analytics pro and I use this constantly to visualize existing data.
Maybe you really want to get in the weeds and do something with Amazon SageMaker. SageMaker allows you to build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. This might have a bit of a learning curve, but there's also a feature called Amazon SageMaker Canvas. In my opinion this is our most underrated service. It expands access to machine learning (ML) by providing business analysts with a visual point-and-click interface that allows them to generate accurate ML predictions on their own — without requiring any machine learning experience or having to write a single line of code.
All in all, it really depends on what your goal is, what your data looks like, and what your abilities are. Feel free to click through our current offerings and see what interests you. We have tons of Quick Starts and Free Trainings to help you get started and of course you can request help through your AWS console or right here on re:Post!
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