IT teams in the life sciences have always been at the forefront of employing modern technology. From ELNs, LIMS, SDMSs, and Cloud storage, to Data Lakes and more recently data science technologies for machine learning and AI. While each of these technologies have supported the innovation goals of R&D organizations, analytical data management has remained one of the most challenging data components for the pharmaceutical industry. Analytical data is simply difficult to manage and utilize effectively, and is particularly difficult from an IT perspective due to its heterogeneity, large file sizes, and a lack of systems that handle analytical data in a chemically intelligent way that meets scientific need.
Join us for a webinar in which we will discuss:
- Why traditional IT systems are challenged by analytical data management
- Implications of managing analytical data on the Cloud
- Industry trends for data standardization and how to achieve it today
- How to replace multiple software packages with one and make analytical data accessible throughout your enterprise
- Steps to ensure future viability of analytical data for AI and Data Science