Data Management Solution to Consolidate 30-Year Longitudinal Research Data

Background The Client Challenge

Our client is a leading US research university with a long-standing history and a strong reputation in interdisciplinary medical and social science research. Over the past three decades, the university has conducted a large-scale longitudinal study tracking the long-term health outcomes of over 15,000 participants documenting lifestyle habits, clinical measurements, demographic data, and environmental factors across hundreds of follow up cycles.

Despite the enormous scientific value of this dataset, the university faced a critical challenge: all research data had been collected and stored in hundreds of disconnected Excel and CSV files, each coded according to different internal codebooks and conventions. This made meaningful analysis nearly impossible without significant manual effort. The core challenges included:

• Millions of data entries spread across hundreds of disparate Excel and CSV files with no unified structure
• The same parameters (e.g. age, BMI, blood pressure) coded differently across files and study cycles making cross-file analysis unreliable
• No centralized database or single source of truth for the full 30-year dataset
• Researchers spent hours manually searching and compiling data for each report or analysis request
• No self-service analytics capability every data query required involvement from the IT team
• Risk of data loss and inconsistency growing with each new study cycle added to the existing file-based system

The university partnered with Versich bringing deep expertise in healthcare data analytics and research data management to design and build a centralized data management and analytics solution on the Microsoft technology stack.