As organizations strive to realize the potential of AI, the complexity of modern data environments has grown. Many organizations are dealing with increasing volumes of data from diverse sources (including unstructured formats) while facing persistent challenges such as data silos and manual data transformation efforts. TDWI research indicates that unstructured data collection is mainstream and that a top priority for organizations is to build out a modern data environment to support diverse and distributed data for AI.
To stay competitive, organizations need a modern data platform that supports collaboration across teams, ensures robust security and governance, and provides easy access to data and AI algorithms. One industry that is a good example of where these dynamics are particularly important is life sciences.
From accelerating drug discovery to optimizing clinical trials, organizations in this sector depend on collaboration across diverse teams, often distributed globally, to make data actionable. Yet data silos and integrating diverse data remain significant hurdles, slowing innovation.
Simplify your path to discovery.
See Luma in action by requesting a demo today.