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Today, teams across biopharma suffer from information silos, underutilized data, and inefficient research processes that pose enormous risks to data integrity and shift focus away from higher-value tasks.
Scientists and data scientists waste over 50% of their time manually managing large and complex datasets that are fragmented and in hundreds of different proprietary formats. Data is moved between instruments and informatics systems with USB drives and/or handwritten notes further slowing down innovation.
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