Rasgo

Collaborative Data Preparation for Machine Learning.

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Overview

Rasgo is a collaborative data preparation platform that is designed to help data scientists and ML engineers to create and manage features for their models. It provides a user-friendly interface for exploring data, defining transformations, and generating features. Rasgo is built to work with cloud data warehouses and allows users to collaborate on feature engineering projects.

✨ Key Features

  • Collaborative feature engineering
  • Visual data exploration and transformation
  • Integration with cloud data warehouses
  • Feature discovery and sharing
  • Python SDK for programmatic access

🎯 Key Differentiators

  • Focus on collaborative feature engineering
  • User-friendly, visual interface
  • Deep integration with cloud data warehouses

Unique Value: Accelerates the feature engineering process and improves collaboration among data science teams by providing a user-friendly and collaborative platform for data preparation.

🎯 Use Cases (3)

Feature engineering Data preparation for ML Data science collaboration

✅ Best For

  • Accelerating feature creation for predictive models
  • Improving collaboration between data scientists

💡 Check With Vendor

Verify these considerations match your specific requirements:

  • Teams needing a low-latency online feature store

🏆 Alternatives

dbt Trifacta Scribble Data

Offers a more visual and collaborative approach to feature engineering compared to code-based tools like dbt. It is designed specifically for the needs of data scientists and ML engineers.

💻 Platforms

Web API

🔌 Integrations

Snowflake BigQuery Redshift Databricks

🛟 Support Options

  • ✓ Email Support
  • ✓ Live Chat
  • ✓ Dedicated Support (Enterprise tier)

🔒 Compliance & Security

✓ SOC 2 ✓ GDPR ✓ SSO ✓ SOC 2 Type II

💰 Pricing

Contact for pricing

✓ 14-day free trial

Free tier: NA

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