AWS is excited to announce the general availability of Amazon SageMaker integration in QuickSight. You can now integrate your own Amazon SageMaker ML models with QuickSight to analyze the augmented data and use it directly in your business intelligence dashboards. As a business analyst, data engineer, or data scientist, you can perform ML inference in QuickSight with just a few clicks. This process makes predictions on new data and uses Amazon SageMaker models for different use cases, such as predicting the likelihood of customer churn, scoring leads to prioritize sales activity, and assessing credit risk for loan applications.
Customer use case
Change Healthcare is a leading independent healthcare technology company that provides data and analytics-driven solutions to improve clinical, financial, and patient engagement outcomes in the US healthcare system.

At Change Healthcare “We are leveraging Amazon SageMaker for various machine learning use cases such as reducing overpayment and claim

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