Innovation often comes from taking a fresh look at something you use every day and wondering, “This thing works just fine for its intended purpose, but could it do anything more?” That kind of thinking may one day lead to cars that actively monitor our health, both inside and outside the vehicle. And innovative thought like that has already led to cell phones being used to identify the source – and likely destination – of disease outbreaks. Read about these uses, learn about the growth of courses to educate tomorrow’s data scientists, and get tips on how you can be successful in your big data initiatives.
"Your Next Doctor Might Be Your Car," by Ariel Schwartz, Fast Company
The typical car has many sensors to measure the performance and maintenance of the vehicle itself. But for two years, the USC School of Cinematic Arts and BMW have been toying with more personal sensors in a tricked-out Mini Cooper. Other groups as USC are imagining creative ways to apply vehicle sensors in the future to monitor and aid our health.
"Can cell phone data help contain malaria spread?" DNA, Oct. 12
According to research cited in this article, malaria kills about 1 million people each year and threatens over 3 billion globally. An important factor in treatment and prevention is tracking human carriers. Reseachers overlaid a malaria map onto data collected from over 14 million cell phone users to identify areas of high risk for each the source or spread of the disease.
"Healthcare Execs Must Prepare For Big Data," by Neil Versel, InformationWeek, Oct. 8
Attendees at the Body Computing Conference heard one speaker proclaim, “Big data is going to change the rules of IT departments and beyond.” From the immense amount of data stemming from genome sequencing to real-time data flowing from patient-monitoring devices and the continued emphasis on electronic health records, healthcare is facing rapid change.
RELATED: "Big Data In Healthcare: Yes!!" by Lorraine Fernandes, gives five examples of areas where big data can play a helpful role in healthcare settings, from reducing fraud to aiding research and collaborative care. This blog post also provides a link to a recent article by Fernandes in the Journal of AHIMA, “Big Data, Bigger Outcomes.”
"Grad schools add big-data degrees," by Patrick Thibodeau, Computerworld, Oct. 8
The lack of people trained in data science and big data has been a source of steady conversation for months. The world of higher education has taken notice, and several colleges and universities are rolling out advanced degree programs, which are being met with strong interest.
"Is big data the crack cocaine of millennial scientists?" by Tim McElligott, FierceBigData, Oct. 4
Halfway through this post, when you are starting to shake your head at the curmudgeonly McElligott, he swings it around, ending with a rationale on why millenials are “tailor made for big data.”
RELATED: "Fording the Stream to Big Data Education," by David Pittman
While it’s good to see grad programs popping up for big data, it's better to get an earlier start in undergrad programs. The University of Montana is doing just that. Watch my interview with two visionaries who created and launched a stream computing course this semester.
"The One Tool You Need To Make Big Data Work: The Pencil," by Matt Ariker, Forbes, Oct. 9
Ariker calls the pencil “a simple but powerful tool to evade the Big Data trap of analysis paralysis.” His advice? Plan before acting. Set goals and expectations, define what success looks like, determine milestones. Solid advice.
RELATED: “Selecting Your First Big Data Project,” by Tom Deutsch, gives additional advice and points to ponder about how to select the team and technology for your project.
"10 Big Data Sites to Watch," Gil Press, Foreign Policy, Oct. 8
If you’re within the sound of my keystrokes, you have an interest in all things big data. Trove understands that too, so they rounded up their 10 favorite sites that aren’t by companies developing or selling big data technologies. The sites include sources for data, education, job listings, and much more. It’s worth a bookmark.
Leave a comment. What was your favorite item from the big data beat this week? Was it one of the above or something I missed entirely?
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