Modern laboratory information management system (LIMS) software has far surpassed the performance of traditional paper-based record-keeping, enabling laboratories to automate the collection of data, avoid the generation of siloed data whilst improving data integrity. That said, until now, data accessibility has been a challenge because the lab operator’s relationship to data is usually prescribed by preset LIMS features. Using data science algorithms, it is now possible to process and integrate all LIMS and enterprise data to provide valuable insights and timely, meaningful recommendations.
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