How to Mine Scientific Business Intelligence 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.

Next: Move Collaboration to the Cloud >>

>>> More Cloud Computing Articles          >>> More By Frank Brown