In his young career, Jeffrey Hammerbacher has been a scout on the frontiers of the data economy.
In 2005, Mr. Hammerbacher, then a freshly minted Harvard graduate, did what many math and computing whizzes did. He went to Wall Street as a “quant,” building math models for complex financial products.
Looking for a better use for his skills, Mr. Hammerbacher departed to Silicon Valley less than a year later and joined Facebook. He started a team that began to mine the vast amounts of social network data Facebook was collecting for insights on how to tweak the service and target ads. He called himself and his co-workers “data scientists,” a term that has since become the hottest of job categories.
Facebook was a fabulous petri dish for data science. Yet after two and a half years, Mr. Hammerbacher decided it was time to move on, beyond social networks and Internet advertising. He became a founder of Cloudera, a start-up that makes software tools for data scientists.
Then, starting last summer, Mr. Hammerbacher, who is now 30, embarked on a very different professional path. He joined the Mount Sinai School of Medicine in Manhattan as an assistant professor, exploring genetic and other medical data in search of breakthroughs in disease modeling and treatment.
The goal, Mr. Hammerbacher said, is “to turn medicine into the land of the quants.”
The story is the same in one field after another, in science, politics, crime prevention, public health, sports and industries as varied as energy and advertising. All are being transformed by data-driven discovery and decision-making. The pioneering consumer Internet companies, like Google, Facebook and Amazon, were just the start, experts say. Today, data tools and techniques are used for tasks as varied as predicting neighborhood blocks where crimes are most likely to occur and injecting intelligence into hulking industrial machines, like electrical power generators.
Big Data is the shorthand label for the phenomenon, which embraces technology, decision-making and public policy. Supplying the technology is a fast-growing market, increasing at more than 30 percent a year and likely to reach $24 billion by 2016, according to a forecast by IDC, a research firm. All the major technology companies, and a host of start-ups, are aggressively pursuing the business.
Demand is brisk for people with data skills. The McKinsey Global Institute, the research arm of the consulting firm, projects that the United States needs 140,000 to 190,000 more workers with “deep analytical” expertise and 1.5 million more data-literate managers, whether retrained or hired, by 2020.
Yet the surveillance potential of Big Data, with every click stream, physical movement and commercial transaction monitored and analyzed, would strain the imagination of George Orwell. So what will be society’s ground rules for the collection and use of data? How do we weigh the trade-offs involving privacy, commerce and security? Those issues are just beginning to be addressed. The debate surrounding the recent disclosure that the National Security Agency has been secretly stockpiling telephone call logs of Americans and poring through e-mail and other data from major Internet companies is merely an early round.
Big Data is a vague term, used loosely, if often, these days. But put simply, the catchall phrase means three things. First, it is a bundle of technologies. Second, it is a potential revolution in measurement. And third, it is a point of view, or philosophy, about how decisions will be — and perhaps should be — made in the future.
In 2005, Mr. Hammerbacher, then a freshly minted Harvard graduate, did what many math and computing whizzes did. He went to Wall Street as a “quant,” building math models for complex financial products.
Looking for a better use for his skills, Mr. Hammerbacher departed to Silicon Valley less than a year later and joined Facebook. He started a team that began to mine the vast amounts of social network data Facebook was collecting for insights on how to tweak the service and target ads. He called himself and his co-workers “data scientists,” a term that has since become the hottest of job categories.Facebook was a fabulous petri dish for data science. Yet after two and a half years, Mr. Hammerbacher decided it was time to move on, beyond social networks and Internet advertising. He became a founder of Cloudera, a start-up that makes software tools for data scientists.
Then, starting last summer, Mr. Hammerbacher, who is now 30, embarked on a very different professional path. He joined the Mount Sinai School of Medicine in Manhattan as an assistant professor, exploring genetic and other medical data in search of breakthroughs in disease modeling and treatment.
The goal, Mr. Hammerbacher said, is “to turn medicine into the land of the quants.”
The story is the same in one field after another, in science, politics, crime prevention, public health, sports and industries as varied as energy and advertising. All are being transformed by data-driven discovery and decision-making. The pioneering consumer Internet companies, like Google, Facebook and Amazon, were just the start, experts say. Today, data tools and techniques are used for tasks as varied as predicting neighborhood blocks where crimes are most likely to occur and injecting intelligence into hulking industrial machines, like electrical power generators.
Big Data is the shorthand label for the phenomenon, which embraces technology, decision-making and public policy. Supplying the technology is a fast-growing market, increasing at more than 30 percent a year and likely to reach $24 billion by 2016, according to a forecast by IDC, a research firm. All the major technology companies, and a host of start-ups, are aggressively pursuing the business.
Demand is brisk for people with data skills. The McKinsey Global Institute, the research arm of the consulting firm, projects that the United States needs 140,000 to 190,000 more workers with “deep analytical” expertise and 1.5 million more data-literate managers, whether retrained or hired, by 2020.
Yet the surveillance potential of Big Data, with every click stream, physical movement and commercial transaction monitored and analyzed, would strain the imagination of George Orwell. So what will be society’s ground rules for the collection and use of data? How do we weigh the trade-offs involving privacy, commerce and security? Those issues are just beginning to be addressed. The debate surrounding the recent disclosure that the National Security Agency has been secretly stockpiling telephone call logs of Americans and poring through e-mail and other data from major Internet companies is merely an early round.
Big Data is a vague term, used loosely, if often, these days. But put simply, the catchall phrase means three things. First, it is a bundle of technologies. Second, it is a potential revolution in measurement. And third, it is a point of view, or philosophy, about how decisions will be — and perhaps should be — made in the future.
by Steve Lohr, NY Times | Read more:
Image: uncredited
