What do you think of when you hear the word predict? Before I started grad school, I probably would have answered that question with crystal balls and fortune tellers. In reality, scientific predictions are calculations based on empirical evidence - not gut feelings. When used appropriately, they play an integral role in expediting academic and industrial workflows, reducing instrument time, and ultimately, saving money.
Analytical data plays a critical role in R&D by supporting critical decision-making on a daily basis. Whether a synthetic chemist is looking to see if their reaction yielded the product they expected, a group of scientists in development are building an impurity control strategy, or experts in manufacturing are collecting data for regulatory submissions, applications of analytical data are ubiquitous. At a time when the volume of insight-rich data one can gather is extraordinary, chemists working in academic research, industry, and non-profit organizations alike face regular challenges in managing and sharing their data.