How to Mine Scientific Business Intelligence in the Cloud
To transform today's deluge of data into knowledge that drives innovation, scientific organizations need to bring back the contextually-rich collaboration that existed at the company lunch table. Scientific business intelligence solutions are services-based, flexible and designed to handle the complexities of modern research environments. Here, Knowledge Center contributor Frank Brown explains how scientific business intelligence can empower researchers to work together more effectively and make new discoveries in the cloud.
Before the rise of the mammoth database, before e-mail, electronic laboratory notebooks (ELNs), and global Centers of Excellence, R&D innovation was centered on personal communication at the company lunch table. It was here that project team leaders-such as the head chemist, pharmacologist, biologist and other select stakeholders-would gather to share their knowledge. The rich insights that resulted led to a significant number of discoveries in areas ranging from pharmaceuticals and consumer packaged goods, to specialty chemicals and heavy manufacturing.
Thanks to the swift pace of technological change, our ability to generate data has increased exponentially. The problem is that there is too much content and not enough context. Raw information dumped into data warehouses has replaced the knowledge-driven categorization and intelligence capabilities that dominated the lunch table.
Disjointed processes and disparate data silos [a product lifecycle management application (PLM) here, a chemistry system here] have replaced collaborative project ownership and decision making. As a result, the most valuable information is often hidden in a deluge of data, inaccessible to the researchers who need them and disconnected from other relevant sources of knowledge.
To usher in a new era of innovation, R&D organizations need to re-create the open, collaborative atmosphere that existed at the company lunch table, but on a scale that embraces the breadth and complexity of today's global scientific information landscape. Here's how.