Data integration in the laboratory

In laboratories, data is generated in many places and in different formats. Measuring devices generate raw data, QA systems manage sample information, ERP systems provide material master data and many teams also work in Excel. Without targeted integration, each system stands alone, which leads to loss of information, search effort and inconsistencies. Data integration combines these sources of information technically and in terms of content, so that relationships such as project, batch, process parameters and measurement results are automatically linked. This is the only way to create complete data sets that can be analyzed, compared and automatically evaluated. Modern platforms enable this consistent flow of data and thus create the basis for AI, automation and reproducible decisions.