Data Hub

Saama's Data Hub is a powerful clinical data ingestion and centralization solution designed for life sciences organizations conducting clinical research. It brings together clinical, operational, and financial data from any source into a single, standardized platform, eliminating the manual data aggregation and reconciliation processes that slow teams down. Data Hub is built for data managers, study managers, and clinical teams who need to generate insights from their data rather than spend time managing it.

As part of Saama's Clinical Data Foundation, Data Hub is purpose-built to handle high volumes of data at scale — from individual studies to large, global trial portfolios — and has been shown to deliver a 35% reduction in time to data discovery.

Key Benefits

• Use any data capture source: Clinical teams gain the flexibility to capture data from any source, supported by 40+ pre-built connectors and file-based ingestion options.
• Streamlined data access: Clinical, operational, and financial data are centralized and standardized in one location, enabling faster insight generation.
• Scalability: Studies can be configured easily and the platform scales seamlessly from a single study to an entire global portfolio.
• Accelerated time to market: Real-time monitoring of study progress helps teams identify and mitigate potential roadblocks before they impact timelines.

Core Features

• Data ingestion: Supports ingestion of both structured and unstructured data, including flat files, in real-time. Accepts data from all standard sources and integrates clinical, operational, and financial data in one place.
• Data standardization: Data is mapped into a standard data review model using 30+ out-of-the-box functions, with the ability to assign different data standards by study or groups of studies.
• Data blinding and masking: Users can upload blinded datasets, mask specific portions of a dataset, and restrict access as needed to maintain data integrity and compliance.
• AI-driven data mapping: AI algorithms predict the correct mapping between source data and the target standard, reducing manual effort and improving accuracy.
• Secure, role-based access: Ensures that critical business functions have appropriate data access while maintaining robust data security and privacy controls.
• SQL console: Enables users to run custom queries across multiple data layers securely, with direct access to raw data that can be joined and analyzed using SQL syntax, all within role-based privacy controls.
• Global Metadata Repository: A centralized library of reusable metadata maps, custom functions, and reference data that keeps transformations consistent across studies.
• Study Configuration Promotion: Validated workflows allow tested library and study configurations to be promoted between environments, speeding onboarding and reducing manual errors.

Data Hub integrates seamlessly within Saama's broader Clinical Data Foundation platform, working alongside tools such as Smart Data Quality, Operational Insights, and Patient Insights. It is designed to support organizations seeking to accelerate trial timelines, improve decision-making, and maintain data security and compliance across their clinical research operations.