STORMSPLITTER | 12 years ago | on: Big data: are we making a big mistake?
I enjoyed your post, nemesisj.
Within your field of longitudinal patient data, if I am correct in what you have written, your large datasets simply have a new name, paranthetically Big Data, and that you could get what you need to save money without the newfangled algorithms. Within academic bioscience, I think there is great consensus on what Big Data is - I have not seen much argument at all; however, it is still very hard to define within that field. The best I can do, over this cup of coffee, is to state that there is a clear distinction between the study of a gene, up to a few pathways vs. computational analysis of multiple OMICS (genomics, metabolomics and proteomics) datasets. I know that definition is terribly lacking and I am fighting the urge to delete it for the sake of getting the post completed. Anyway, Big Data is clearly changing the academic biosciences through the funding trend. That is, grants with a computational focus, or sub focus, certainly seem to be doing comparably well. I mention this because todays academic funding trends influence the direction of tomorrows startups as those being trained are disproportionally within the better funded labs, and draw upon their previous experience when forming companies. So, I personally believe this Big Data thing, however it is best defined over all, or within a given field, is in some way something new, and will continue to shape the startup sphere for years to come, especially in the areas of genomics, metabolomics and proteomics. This is my first post: ) Thanks!