Faster, better, reproducible: Lab automation is not complete without data analysis

ELN and LIMS provide a structured workflow in the lab, but data analysis often remains a manual, error-prone and time-consuming process. Many researchers still rely on spreadsheets and disparate scripts, leading to inefficiencies, lack of reproducibility and difficulties in scaling up.

In this session I will show how a standardized, automated approach can transform data analysis. By eliminating manual steps, workflow becomes more efficient, results more reliable, and documentation easier to trace. Automation ensures that analyses are no longer dependent on individual expertise, but are performed robustly and repeatably.

With practical examples from the life sciences, I show how researchers can go from raw data to useful insights faster, without compromising on quality and accuracy. No more separate scripts, but an integrated system that automatically performs analyses, records results and reports directly.

Lab automation is not complete without automated data analysis. This is the step needed to make research more efficient, consistent and future-proof.

– Lars-Eric Fielmich, PhD –