The most challenging barrier for R&D teams to make use of machine learning and artificial intelligence is not using the best technique, but having access to clean, structured data. Current data systems often fall short, with inputs and outputs not connected, ambiguity in naming, and under-specification of results. As a result, machine learning wins are isolated to teams working on specialized projects.
Watch this webinar to learn the framework for a modern, structured, data management system. When a traditional ELN or LIMS is used, teams often still work in spreadsheets, making it impossible for the entire company to benefit from their learnings. A modern system will move scientists out of spreadsheets, and create a set of data that the entire company can benefit from.
Key Learning Objectives:
- How modern data management systems differ from legacy LIMS and ELN systems
- Why structured data, and not proprietary algorithms, leads to success at innovative companies making use of machine learning.
- The prerequisites for making machine learning work across an organization
Who Should Attend:
- R&D Executives looking to speed up their teams workflow
- Team Leaders
- Lab Managers