Sunday, February 12, 2012

Another Ode To Big Data

New York Times: The Age of Big Data
an explosion of data — Web traffic and social network comments, as well as software and sensors that monitor shipments, suppliers and customers — to guide decisions, trim costs and lift sales ...... 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 ...... The story is similar in fields as varied as science and sports, advertising and public health — a drift toward data-driven discovery and decision-making. “It’s a revolution” ...... the march of quantification, made possible by enormous new sources of data, will sweep through academia, business and government. There is no area that is going to be untouched ...... Welcome to the Age of Big Data. ...... data a new class of economic asset, like currency or gold ...... Big Data has the potential to be “humanity’s dashboard,” an intelligent tool that can help combat poverty, crime and pollution. Privacy advocates take a dim view, warning that Big Data is Big Brother, in corporate clothing. ........ a lot more data, all the time, growing at 50 percent a year, or more than doubling every two years ....... It’s not just more streams of data, but entirely new ones. ....... there are now countless digital sensors worldwide in industrial equipment, automobiles, electrical meters and shipping crates. They can measure and communicate location, movement, vibration, temperature, humidity, even chemical changes in the air. ........ the Internet of Things or the Industrial Internet. ....... Data is not only becoming more available but also more understandable to computers. Most of the Big Data surge is data in the wild — unruly stuff like words, images and video on the Web and those streams of sensor data. It is called unstructured data and is not typically grist for traditional databases. ........ the computer tools for gleaning knowledge and insights from the Internet era’s vast trove of unstructured data are fast gaining ground. At the forefront are the rapidly advancing techniques of artificial intelligence like natural-language processing, pattern recognition and machine learning ....... The wealth of new data, in turn, accelerates advances in computing — a virtuous circle of Big Data. Machine-learning algorithms, for example, learn on data, and the more data, the more the machines learn. Take Siri ....... The microscope, invented four centuries ago, allowed people to see and measure things as never before — at the cellular level. It was a revolution in measurement. ....... Data measurement.... is the modern equivalent of the microscope. Google searches, Facebook posts and Twitter messages, for example, make it possible to measure behavior and sentiment in fine detail and as it happens. ....... decisions will increasingly be based on data and analysis rather than on experience and intuition. “We can start being a lot more scientific” ........ the low-budget Oakland A’s massaged data and arcane baseball statistics to spot undervalued players. Heavy data analysis had become standard not only in baseball but also in other sports, including English soccer, well before last year’s movie version of “Moneyball,” starring Brad Pitt. ...... Walmart and Kohl’s, analyze sales, pricing and economic, demographic and weather data to tailor product selections at particular stores and determine the timing of price markdowns. Shipping companies, like U.P.S., mine data on truck delivery times and traffic patterns to fine-tune routing. ....... Police departments across the country, led by New York’s, use computerized mapping and analysis of variables like historical arrest patterns, paydays, sporting events, rainfall and holidays to try to predict likely crime “hot spots” and deploy officers there in advance. ....... data-guided management is spreading across corporate America and starting to pay off. ...... studied 179 large companies and found that those adopting “data-driven decision making” achieved productivity gains that were 5 percent to 6 percent higher than other factors could explain. ...... The predictive power of Big Data is being explored — and shows promise — in fields like public health, economic development and economic forecasting. Researchers have found a spike in Google search requests for terms like “flu symptoms” and “flu treatments” a couple of weeks before there is an increase in flu patients coming to hospital emergency rooms in a region (and emergency room reports usually lag behind visits by two weeks or so). ....... sentiment analysis of messages in social networks and text messages — using natural-language deciphering software — to help predict job losses, spending reductions or disease outbreaks in a given region. The goal is to use digital early-warning signals to guide assistance programs in advance to, for example, prevent a region from slipping back into poverty. ...... trends in increasing or decreasing volumes of housing-related search queries in Google are a more accurate predictor of house sales in the next quarter than the forecasts of real estate economists ....... social-network research involves mining huge digital data sets of collective behavior online. Among the findings: people whom you know but don’t communicate with often — “weak ties,” in sociology — are the best sources of tips about job openings. They travel in slightly different social worlds than close friends, so they see opportunities you and your best friends do not. ...... Researchers can see patterns of influence and peaks in communication on a subject — by following trending hashtags on Twitter, for example. The online fishbowl is a window into the real-time behavior of huge numbers of people. ...... Big Data has its perils, to be sure. With huge data sets and fine-grained measurement, statisticians and computer scientists note, there is increased risk of “false discoveries.” ...... “many bits of straw look like needles.” ...... Big Data also supplies more raw material for statistical shenanigans and biased fact-finding excursions. It offers a high-tech twist on an old trick: I know the facts, now let’s find ’em. ..... Data is tamed and understood using computer and mathematical models. These models, like metaphors in literature, are explanatory simplifications. They are useful for understanding, but they have their limits. A model might spot a correlation and draw a statistical inference that is unfair or discriminatory, based on online searches, affecting the products, bank loans and health insurance a person is offered ...... Veteran data analysts tell of friends who were long bored by discussions of their work but now are suddenly curious. .... “The culture has changed” .... “There is this idea that numbers and statistics are interesting and fun. It’s cool now.”

Big Data Democratization By Wolfram Alpha
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