Data Hub

Data Hub is a comprehensive data ingestion solution designed for the clinical research industry. It centralizes and standardizes large volumes of data from various sources, eliminating the need for manual data aggregation and reconciliation. This allows teams to focus on generating insights rather than managing data.

With over 40 pre-built connectors and file-based ingestion, Data Hub offers flexibility in capturing data from any source. It centralizes clinical, operational, and financial data, enabling quick insight generation. The platform is scalable, allowing easy configuration for new studies and supporting both individual and large, global study portfolios.

Data Hub accelerates time to market by providing real-time study progress monitoring, helping to identify and mitigate potential roadblocks. It boasts a 35% reduction in time to data discovery.

Features

• Data ingestion: Supports both structured and unstructured data, including real-time flat file ingestion, integrating clinical, operational, and financial data in one location.
• Data standardization: Maps data into a standard review model using over 30 out-of-the-box functions, with the ability to assign different data standards by study or study groups.
• Data blinding/masking: Allows for the upload of blinded datasets, masking parts of datasets, and restricting access.
• AI-driven data mapping: Utilizes AI algorithms to predict correct mapping between source data and target standards.
• Secure, role-based access: Ensures data access for critical business functions while maintaining security and privacy.
• SQL console: Enables running custom queries across multiple layers securely, providing direct access to raw data for analysis using SQL syntax, while maintaining privacy and role-based controls.