
Cloudera Data Platform (CDP)
The hybrid data cloud for the complete data lifecycle and Enterprise AI.

Accelerate data insights by transforming trapped proprietary datasets into scalable, actionable data streams.

CloudQuant Data Liberator is a data integration platform designed to eliminate traditional data barriers for financial services and other industries. It allows users to access, study, and govern data instantly while maintaining data integrity. The platform transforms proprietary datasets into scalable, actionable data streams without requiring complex infrastructure. It supports zero-copy architecture, enabling direct access to data from existing sources without expensive ETL processes. Key features include time-series native support for point-in-time analysis, historical backtesting, and real-time streaming integration. The platform offers granular entitlements, comprehensive audit trails, and role-based access controls to ensure data security and compliance. Its API-first design facilitates seamless integration with existing workflows, from Python and R to Excel and Tableau.
CloudQuant Data Liberator is a data integration platform designed to eliminate traditional data barriers for financial services and other industries.
Explore all tools that specialize in data governance. This domain focus ensures CloudQuant Data Liberator delivers optimized results for this specific requirement.
Enables direct access to data from existing sources without replication or ETL processes.
Purpose-built for financial, investment, and trading data with native support for point-in-time analysis, historical backtesting, and real-time streaming integration.
Granular entitlements, comprehensive audit trails, and role-based access controls ensure data security and compliance.
Modern native language APIs integrate seamlessly with existing workflows, from Python and R to Excel and Tableau.
Provides example code for Python programming language and Pandas to help quantitative data scientists.
Connect to your existing data stores (e.g., databases, cloud storage).
Define data entitlements and access controls using the platform's governance features.
Integrate data streams into your quantitative analysis environment (e.g., Python, R).
Utilize the platform's API to access live or historical time series data.
Implement in-sample and out-of-sample data ranges for backtesting.
Monitor data usage and audit trails to ensure compliance.
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"Customers praise the platform's ease of integration, data governance capabilities, and time-series native support."
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