Vendor needs to provide research web–based data solution. – High–performance computing: Must provide access to powerful servers with significant processing – Direct high–speed data access: Must offer low–latency, high–throughput access to hosted datasets, enabling efficient querying, data extraction, and integration for big–data research. – Dedicated user storage: Must provide a secure, dedicated user directory for storing programs and output data, along with large temporary/scratch disk space for intermediate processing and computation results. – Multi–user and concurrent processing support: Platform must support simultaneous access by multiple users and allow concurrent execution of multiple jobs without significant performance loss. – Data security and compliance: Must meet institutional and industry–standard security requirements, including user authentication, access controls, encrypted connections, and secure data storage. – Reliability and system uptime: Must ensure high availability, regular system maintenance, backup, and minimal downtime for uninterrupted research access. – Large–scale data handling: Must be capable of handling very large structured and unstructured datasets, including high–volume tables, time–series data, and panel data. – Interoperability and data integration: Must allow cross–dataset linking, merging, and integration across multiple data sources and formats. – Performance optimization: Must support efficient job scheduling, queuing, and workload management to maximize system utilization and user productivity. – User–friendly analytical environment: Must provide both command–line and graphical user interfaces, suitable for beginner and advanced users. – Export and results management: Must allow users to download, export, and archive processed results securely for offline analysis and reporting. – Version control and reproducibility support: Platform should support reproducible research workflows, including version control compatibility a