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Copy of Applications of BIG DATA

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Trilce Estrada

on 2 March 2014

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Transcript of Copy of Applications of BIG DATA

What is BIG DATA used for?
Predicting epidemic outbreaks
Farecast
In 2009
A new flu virus with characteristics from swine flu and bird flu was discovered
No vaccine
HOPE
Slow down
its spread
CDC
Requested that doctors inform them of new flu cases. Yet the picture of the pandemic that emerged was always a week or two out of date.
The authors explained how Google could “predict” the spread of the winter flu in the United States, not just nationally, but down to specific regions and even states. The company could achieve this by looking at what people were searching for on the Internet.
While the Googlers guessed that the searches might be aimed at getting flu information— typing phrases like “medicine for cough and fever”— that wasn’t the point: they didn’t know, and they designed a system that didn’t care. All their system did was look for correlations between the frequency of certain search queries and the spread of the flu over time and space.
Mayer-Schonberger, Viktor; Cukier, Kenneth (2013-03-05).
Big Data: A Revolution That Will Transform How We Live, Work, and Think
In 2003 Oren Etzioni needed to fly from Seattle to Los Angeles for his younger brother’s wedding. Months before the big day, he went online and bought a plane ticket ...
An airplane seat is a commodity. Yet the prices vary wildly, based on a myriad of factors that are mostly known only by the airlines.

Etzioni concluded that he didn’t need to decrypt the rhyme or reason for the price differences. Instead, he simply had to predict whether the price being shown was likely to increase or decrease in the future.
Etzioni was determined to figure out a way for people to know if a ticket price they see online is a good deal or not
All it requires is analyzing all the ticket sales for a given route and examining the prices paid relative to the number of days before the departure.
The model had no understanding of why, only what. That is, it didn’t know any of the variables that go into airline pricing decisions, such as number of seats that remained unsold, seasonality, or whether some sort of magical Saturday-night-stay might reduce the fare. It based its prediction on what it did know: probabilities gleaned from the data about other flights.
The little project evolved into a venture capital– backed startup called Farecast.
By 2008 he was planning to apply the method to other goods like hotel rooms, concert tickets, and used cars: anything with little product differentiation, a high degree of price variation, and tons of data.
Microsoft came knocking on his door, snapped up Farecast for around $110 million, and integrated it into the Bing search engine.
Mayer-Schonberger, Viktor; Cukier, Kenneth (2013-03-05).
Big Data: A Revolution That Will Transform How We Live, Work, and Think
Most of this material was extracted from
Mayer-Schonberger, Viktor; Cukier, Kenneth (2013-03-05).
Big Data: A Revolution That Will Transform How We Live, Work, and Think

Consumer Price Index
CPI is used to calculate the inflation rate and it is crucial for investors and businesses.

The Federal Reserve considers it when deciding whether to raise or lower interest rates.

Companies base salary increases on inflation.

The federal government uses it to index payments like Social Security benefits and the interest it pays on certain bonds
To get the figure, the Bureau of Labor Statistics employs hundreds of staff to call, fax , and visit stores and offices in 90 cities across the nation and report back about 80,000 prices on everything from tomatoes to taxi fares. Producing it costs around $ 250 million a year
But by the time the numbers come out, they’re already a few weeks old.

As the 2008 financial crisis showed, a few weeks can be a terribly long lag.

Decision-makers need quicker access to inflation numbers in order to react to them better
2 economists from MIT, Alberto Cavallo and Roberto Rigobon, came up with a big-data alternative.

Using software to crawl the Web, they collected half a million prices of products sold in the U.S. every single day.

The project was able to detect a deflationary swing in prices immediately after Lehman Brothers filed for bankruptcy in September 2008, while those who relied on the official CPI data had to wait until November to see it.
Product association
Retailers
The correlations even let the retailer estimate the due date within a narrow range, so it could send relevant coupons for each stage of the pregnancy.
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