Description
Kaskada is a machine learning platform specifically designed for event-based data and time-based behavior analysis. The platform enables data scientists to build accurate, real-time feature transformations that capture temporal relationships and sequential patterns in user or entity behavior. By providing a specialized framework for time-aware feature engineering, Kaskada addresses the unique challenges of building predictive models for user behavior, customer journeys, and event-driven processes. The platform's focus on temporal feature computation helps organizations develop more accurate models for recommendation, personalization, fraud detection, and other time-sensitive applications.
Key Features
- Time-aware feature engineering
- Event-based data processing
- Real-time feature computation
- Temporal pattern recognition
- Point-in-time correctness
Use Cases
- Customer journey analysis
- Real-time personalization
- Fraud prevention
- User behavior prediction
- Sequential event modeling
Pricing Model
Usage-based pricing with enterprise options
Integrations
Event streaming platforms, Data warehouses, Feature stores, Machine learning frameworks, Production serving systems
Target Audience
Data scientists, Machine learning engineers, Product analysts, Risk modeling teams, Customer intelligence specialists
Launch Date
2020
Available On
Cloud service, Development environments, Production pipelines
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