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Case Study

Beyond JSON: Centralizing, Modeling, and Aggregating Instrument Data to Enable Deeper Analysis

Beyond JSON: Centralizing, Modeling, and Aggregating Instrument Data to Enable Deeper Analysis

Beyond JSON: Centralizing, Modeling, and Aggregating Instrument Data to Enable Deeper Analysis

Dotmatics
Pages 4 Pages

A large biopharma organization needed to standardize and integrate data from a wide range of scientific instruments to enable deeper analysis and better data contextualization across R&D teams. Existing approaches, including basic JSON conversion, were insufficient to model and connect complex experimental outputs. By implementing Dotmatics Luma, the company automated data acquisition from thousands of instruments and applied advanced parsing, modeling, and integration capabilities. The solution supported complex analysis pipelines across diverse experiments and instrument types. Deployment was completed far faster than expected, with more than 2,000 instruments connected within six months. As a result, teams gained improved analysis capabilities, better data integration, and greater flexi

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