But as the number of specialties grows, and as people increasingly move and change health plans, it becomes harder to know a patient’s history. A typical hospital patient now has 11 medical charts and takes 14 medicines. Keeping track of even this relatively trivial volume of data is overwhelming doctors. Medical errors are proliferating and killing thousands.

As data from genomic and proteomic applications migrate from researchers’ lab benches and become standard patient treatment protocols, we can expect to see much more tailored medical diagnosis, prescription and treatment profiles. Silicon chips covered with little strands of DNA sometimes are able to show which genes are turned on or off during various normal and disease states. Their use is growing 65 percent per year. Given that many experiments have to be continuously repeated because findings are dependent on age, time and environment, and given that a single experiment can generate a half billion data points, a great deal of data can accumulate very quickly and overwhelm researchers if they lack strong IT-analysis support.

Hospitals, pharmacists, doctors and patients will have to manage and triage ever-growing volumes of complex data in cost-effective ways. As profiles become more predictive and personalized, privacy will become a key issue. We will face complex questions as large databases go online and become more accessible. Who should have access to data about potentially disabling diseases, ones that we may contract at some time in the future, but that have not yet appeared within our bodies? For instance, if you have a BRCA-1 or BRCA-2 gene, you may be more predisposed than someone else to breast cancer. Do you want your employer and your insurance company to know that? Probably not. So who should manage and have access to your data? And what do you do if your risk profile changes significantly because of tests you have already taken but that had not yet been seen as key predictors given current genetic knowledge?

Until quite recently, life sciences had not been large-scale drivers of global data generation and storage. However, several computer, Internet, software and storage companies are beginning to see life sciences as a key opportunity for growth. Those who get literate in life code are likely to have many more job opportunities, and they may be equipped to make more intelligent decisions in areas as disparate as portfolio management, personal health, insurance and computer networking possibilities.

Are you ready?