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Collaborative Self -Serve
Advanced Analytics and Data Science

Connect, combine, manage and understand all
the data from multiple sources on one single platform.

Connect to various Data Sources

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Conduct analytics and implement Machine Learning algorithms across various engines

Seamlessly view your ML models and connect to MLflow.

View your ML models, compare them,
and use them for Predictions

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Feature
Importance

This is an example of the most significant features required for building a churn prediction ML Model for Telco customer

Model
Information

View the Model Summary, Feature Importance, Training Metrics, Test Metrics, Confusion Matrix, ROC curve and other info

Models
Stats

View the Model execution statistics like count of models by category, technology and workflows

Visualize your data at scale

View your data in Charts, Maps etc. Bring them together
onto Report from various executions. Seamlessly build dashboards to interact with your data.

Execute on various platforms

Execute data preparation, analytics, visualizations and machine
learning algorithms seamlessly on the cloud or on-premise.

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Seamlessly Collaborate with Teams across the Tech Stack

Work together on projects, create analytics, study your data and
build ML models. Share execution results and comparisons

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