Big Data: A Revolution That Will Transform How We Live, Work, and Think Author: Viktor Mayer-Sch?nberger | Language: English | ISBN:
B009N08NKW | Format: PDF
Big Data: A Revolution That Will Transform How We Live, Work, and Think Description
A revelatory exploration of the hottest trend in technology and the dramatic impact it will have on the economy, science, and society at large.
Which paint color is most likely to tell you that a used car is in good shape? How can officials identify the most dangerous New York City manholes before they explode? And how did Google searches predict the spread of the H1N1 flu outbreak?
The key to answering these questions, and many more, is big data. “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior.
In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing.
- File Size: 2022 KB
- Print Length: 257 pages
- Page Numbers Source ISBN: B00BOPF550
- Publisher: Eamon Dolan/Houghton Mifflin Harcourt; Reprint edition (March 5, 2013)
- Sold by: Amazon Digital Services, Inc.
- Language: English
- ASIN: B009N08NKW
- Text-to-Speech: Enabled
X-Ray:
- Lending: Not Enabled
- Amazon Best Sellers Rank: #8,162 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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in Books > Business & Money > Industries & Professions > Information Management - #2
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The precise definition of what constitutes big data does not exist, it is a term used to refer to the capture of enormous amounts of different types of data that often seems to be unrelated. Yet, that imprecise definition is part of the strength of using big data to make better decisions.
In the days when only small samples could be taken for analysis due to the cost, it was critical that everything be done right, the items in the sample must be randomly chosen and care had to be taken to eliminate any extreme outliers that would skew the result. This also meant that the models had to be very well constructed, for if the model was not applicable, the final results could be worthless or even have negative consequences.
The concept of big data basically means that all the data is examined to look for common characteristics. Outliers are included and are of less significance for they will be drowned out by the enormous number of data points in the middle. One of the examples of the use of big data is the prediction of high fevers in infants. Rather than developing a model for the events that would include many assumptions, not all of which are correct, the immediate history of the children that develop high fevers is examined. All of the vital signs and other data collected about the infants are then examined to determine if there are any common indicators that could be used as predictors. The data analysts are not trying to establish causality, only traits present before the events.
Doing this means that only the data matters, emotion and experience are almost insignificant. The authors describe many examples of where big data has been used to predict and prioritize; one of the most interesting examples is the development of translation software.
The book opens by relating how Google, on its own initiative, devised a means to track the spread and intensity of flu prior to the 2009 flu season. Their methodology began by comparing the 50 million most common American search terms with CDC data on the spread of seasonal flu between 2003 and 2008. Google's software found a combination of search terms that, appropriately weighted, strongly correlated with official data. However, unlike the CDC, Google was able to make those assessments in real time, not a week or two later.
Oren Etzioni, frustrated to learn that many passengers booking a flight after he had, were able to pay less - contrary to conventional wisdom. He then 'scraped' information from a travel website from a 41-day period to forecast whether a price was a good deal or not, founding Farecast to offer this new ability. Etzioni next went on to improve the system by digesting data from a travel stie that covered most American commercial routes for a year - nearly 200 billion flight-price records. Before expanding to hotel rooms, concert tickets and used cars, Microsoft snapped up his firm ($110 million) and incorporated it into it Bing.
New processing technologies like open-source Hadoop allow managing far larger quantities of data. Hadoop uses a computational paradigm named MapReduce (by Google) to divide an application into many small fragments, each of which may be executed on any computer node in a cluster. Visa was able to reduce processing time for two years worth of data (73 billion transactions) from 1 month to 13 minutes using Hadoop.
The authors define 'big data' as things that can be done on a large scale that cannot be done on a smaller one, and see it as offering a major transformation.
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