Item: Amazon SageMaker
Rating: 9
Author: Verified User

Overall Satisfaction with Amazon SageMaker

Use Cases and Deployment Scope

Amazon SageMaker is currently being used by our analytics and technology groups but managed by the associates at our firm. It addresses the business problems of reporting and having one ultimate software of data and analysis that can be used across locations and employees. It allows for one place to store the best algorithms for predicting data on cases and court trials.It also provides examples on actual data sets that can be used, algorithms and easy to run notebooks.

Pros and Cons

Pros

Provides the basis for developing algorithms and data without going very deep into the actual development.
Amazon software and so can be used with other Amazon software your organization already uses.
Training and on boarding of the software and customer service was great to work with.

Cons

Searching and descriptions can be easier to read and interpret.
Training modules and customer service training representative could make on boarding employees easier.

Return on Investment

Easily integrates with our existing workflow
Quick to get us results and reporting back.
Database of algorithms and models already there for you to use.

Alternatives Considered

Amazon SageMaker took the heavy lifting out of building and creating models. It allowed for our organization to use our current system for integration and essentially added on a feature to help all levels of Data scientists and IT professionals in our department and company as a whole. The training was simple as well.

Likelihood to Recommend

SageMaker is well suited for an organization with a robust IT department that might not be as specifically well versed in model building and deployment features. It has built in algorithms and models as well as computations that lay the framework for what our department uses this tool for. It allows our team to get things done whether they are very experienced data scientists or a recent IT new hire who might not know all the ropes yet. They are both able to dive in and develop models and algorithms because the foundation is already there. It is also well suited for a company that uses amazon already as the integration is very easy. I would say the integration might be harder for an organization that does not use Amazon or a smaller organization that might not need as much heavy data or reporting.

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