Metadata, such as instrument settings, last day of service, experiment time, and other information, are not tracked. Raw data is lost and analyses cannot be modified or run again without significant effort. Meta-analyses are difficult because of the lack of traceability. Scientists' productivity suffers even if they have to enter the primary analysis results. Raw data is stored in the cloud, and analysis can be automated with traceability. Data can then be used to create ELNs/LIMSs, Excel, analysis apps, and pipelines - any kind of data. This data lake is also created as we go. Your raw data, analyzed and metadata as well as any internal data from intergrated apps are all saved in one cloud data lake. Run automatic analyses and add metadata automatically. Push results into any app, pipeline, or back to instruments for control.