Visier’s data analytics group enhances their model performance tenfold through transitioning to Amazon SageMaker | AWS Machine Learning Blog

Introduction to Visier and Paycor Collaboration

Visier, with its mission focused on workforce dynamics understanding, collaborates with world-leading enterprise people analytics companies like Paycor to provide informative analytics and actionable insights. With a track record of success, Visier’s predictive analytics have helped organizations such as Providence Healthcare in retaining critical employees and saving significant costs by preventing attrition.

Recognition and Success of Visier

Visier’s innovative approach to people analytics has earned recognition from trusted sources like Sapient Insights Group and Gartner. Over 50,000 organizations in 75 countries use Visier’s platform to drive business strategies and achieve better results. The platform’s analytics and predictive capabilities empower users to make data-backed decisions without requiring advanced data science knowledge.

Enhancing Analytics with Amazon SageMaker

Facing challenges with their existing data science tech stack, Visier turned to Amazon SageMaker to revolutionize their analytics and predictive services. By transitioning to an API-based microservices architecture, Visier achieved increased autonomy in deploying changes and releasing updates more frequently. The migration to SageMaker allowed Visier’s data science team to focus on innovation rather than deployment details.

Improving Efficiency and Scalability with SageMaker

Utilizing SageMaker, Visier developed a prediction model validation pipeline that led to a 30% improvement in prediction performance across their customer base. Additionally, they implemented a highly scalable method to generate thousands of customer-specific predictive models efficiently. The integration of SageMaker libraries for model training ensured state-of-art efficiency and scalability.

Innovation and Community Predictions

By leveraging SageMaker’s capabilities, Visier developed a new prediction product called Community Predictions. This product allows smaller organizations access to predictive insights based on a broader community dataset, enhancing their decision-making capabilities. Through the adoption of SageMaker, Visier enabled their end-customers to create their own AI/ML models and drive impactful outcomes.

Conclusion

Visier’s success story with Amazon SageMaker highlights the platform’s effectiveness in enhancing model output, accelerating innovation cycles, and unlocking new opportunities. By exploring SageMaker’s capabilities, businesses can streamline machine learning workflows, scale model deployments, and extract valuable insights from their data to drive impactful business decisions.

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