The new chief executive of Cisco has made the case for the networking giant as a key player in building, securing, and making sense of the nascent Internet of Things.
Cisco predicts that the 15 billion devices connected to the internet now will rise to 25 billion – or maybe even 50 billion – by 2020, as the Internet of Things gathers pace. Internet traffic will triple over the same time as a result, and Cisco expects that around 40 percent of mobile internet traffic will be machine-to-machine communication.
All of this will create big changes for how enterprises manage data, said Cisco CEO Chuck Robbins: instead of hauling all that information back to a data center, some of the analysis of that data will be distributed across the network.
Speaking at an event at Cisco’s headquarters in San Jose, California, his first major presentation since taking over as CEO, Robbins said: “You need a very intelligent network infrastructure to make that happen. So now we will have not just data centers but remote centers of data. We can’t always depend on taking the data back to the data center and acting on it because it has a shelf-life, it’s perishable, the value only exists for a short period of time.”
Genomics is making headlines in both academia and the celebrity world. With intense media coverage of Angelina Jolie’s recent double mastectomy after genetic tests revealed that she was predisposed to breast cancer, genetic testing and genomics have been propelled to the front of many more minds.
In this new data field, companies are approaching the collection, analysis, and turning of data into usable information from a variety of angles.
What is Genomics?
Genomics is the study of the complete genetic material (genome) of organisms. The field includes sequencing, mapping, and analyzing a wide range of RNA and DNA codes, from viruses and mitochondria to many species across the kingdoms of life. Most pertinent here are intensive efforts to determine the entire DNA sequence of many individual humans in order to map and analyze individual genes and alleles as well as their interactions. The primary goal that drives these efforts is to understand the genetic basis of heritable traits, and especially to understand how genes work in order to prevent or cure diseases.
The amount of data being produced by sequencing, mapping, and analyzing genomes propels genomics into the realm of Big Data. Genomics produces huge volumes of data; each human genome has 20,000-25,000 genes comprised of 3 million base pairs. This amounts to 100 gigabytes of data, equivalent to 102,400 photos. Sequencing multiple human genomes would quickly add up to hundreds of petabytes of data, and the data created by analysis of gene interactions multiplies those further.
Genomics Fuels Personalized Medicine
Personal genomics–understanding each individual’s genome–is a necessary foundation for predictive medicine, which draws on a patient’s genetic data to determine the most appropriate treatments. Medicine should accommodate people of different shapes and sizes. By combining sequenced genomic data with other medical data, physicians and researchers can get a better picture of disease in an individual. The vision is that treatments will reflect an individual’s illness, and not be a one treatment fits all, as is too often true today.
Suggested Reading: Genetics and Genomics in Medicine
A great video to watch
Suggested Link: Big Data-They- Know Everything about You
“They seem to be at an unusual disadvantage,” said Gerry McCartney, system chief information officer and vice president for information technology at Purdue University. Purdue’s Course Signals program has given students, faculty, and administrators more information about student performance since it was piloted during the 2006-07 academic year. Aggregating all of the data from these students and their predecessors creates a useful roadmap showing which course and study strategies work.
McCartney calls Signals a fairly rudimentary product that is already showing remarkable results with traditionally at-risk students and others. It’s not predictive — it simply flags indicators that have contributed to a student’s failure in the past, giving current students the benefit of an early warning.
“It’s like sitting next to somebody who has been through the class before,” McCartney said. “They say ‘I’d do that reading if I were you.’”
Suggested Readings: Good to Great: Why Some Companies Make the Leap…And Others Don’t
Everybody talks about innovation these days, but the word is used so lightly. Every new app, gadget or product feature is now “innovation”. A few decades ago, “innovation” implied a life-changing advance in technology: the transistor, the computer, space flight. Does it mean anything that we speak of innovation more casually today than we did in the past century? Maybe.
In October, 2000, the US Congress mandated this goal: “by 2015, one-third of the operational ground combat vehicles are unmanned.” We haven’t reached that goal. Yes, it’s a tough goal, and yes, Google, Daimler, Mobileye and others are making progress on driverless cars. But still, we didn’t make the goal. It seems a pretty modest goal compared to putting a man on the moon, and we did that in less than nine years, with resources that look mighty primitive by today’s standards.
Suggested Readings: Predictive Analytics For Dummies