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If you think that big data doesn’t play a role in your life, think again. Say that your little one seems under the weather. You Google his symptoms and search for the best cough medicine for kids. Meanwhile, Google aggregates and analyzes search queries, such as “my kid is sick,” in your location to estimate flu activity in the area in real time. These data points then allow Johns Hopkins researchers analyzing Google searches to predict flu outbreaks more quickly than the Centers for Disease Control (CDC).
Or perhaps you just bought a new refrigerator, a GE smart appliance. Thanks to GE’s NewFi System, your fridge will communicate constantly with GE, feeding it data on how often the fridge is opened, what its temperature is, and any imminent mechanical failures. When you call for repairs, the tech will arrive equipped with the parts that GE’s appliance data suggest might need replacing. To confirm, the tech can hook up a laptop to the fridge to analyze diagnostic data.
These are just two scenarios that illustrate how big data and algorithms not only are permeating our lives, but also changing them for the better. We create more data now than ever before with Internet usage, smartphones, social media, transactions, and myriad sensor-equipped devices. In fact, the executive chairman of Google, Eric Schmidt, estimates that we produce in two days the same amount of data amassed from civilization’s start to 2003. Read on to learn more about how big data is revolutionizing the way we live.
The definition of big data varies according to its application, but a recent White House report defined it as the “growing technological ability to capture, aggregate, and process an ever-greater volume, velocity, and variety of data.” In 2013, the world generated four zettabytes of data according to the report. To put that into context, if every person in the U.S. took a digital photo every second of every day for more than a month, those photos combined would equal one zettabyte.
A major driver of big data is the “Internet of Things,” which refers to the ability of devices, from cars to appliances, to communicate with one another through sensors linked to networks. These Internet-connected devices — which will number six billion by 2015, according to Harvard Business Review — generate massive amounts of data with all kinds of potential.
Big data may not be able to determine causation, but it excels at identifying correlation. In medicine, spotting correlations may be all that providers need for taking preventive measures. For example, Canadian researchers analyzed premature babies, monitoring more than 1,000 data points each second. They stunned doctors when they found a correlation between abnormally stable vital signs and a serious fever one day later. While they don’t understand the phenomenon, physicians can now treat to prevent these fevers.
Similarly, researchers from MIT and several other institutions created a computer model using a mountain of discarded EKG data from heart attack survivors. The model helps identify the patients at risk for another heart attack in the next year. Using data-mining and machine-learning, they discovered three abnormalities in EKGs that correspond with an elevated risk of a second heart attack. Normal screening methods examine only 30 seconds of an EKG; this model allows physicians to analyze hours of EKG data to spot red flags.
In a 2002 news briefing, Donald Rumsfeld famously commented that the “unknown unknowns,” or the things that the U.S. doesn’t know that it doesn’t know, of homeland security are the most pernicious. That predicament is ameliorated by big data analytics that can study travel behavior, Internet activity, bank accounts, phone records, and more to spot worrisome patterns. These analytics can identify the people whom we don’t know are affiliated with criminal or terrorist activity — the ones who would otherwise go undetected.
Likewise, something as seemingly innocuous as your employee ID badge can generate big data that helps officials identify criminal activity. Fraud-spotting algorithms look for aberrations in the times that employees badge into secured buildings, such as suddenly coming in at night or on weekends. In fact, badging patterns are one of the variables that software funded by the CIA examines in identifying insider trading.
Big data can help pinpoint energy leeches in buildings and homes to reduce electricity usage. Consider computer science professor Shwetak Patel, who invented a device called ElectriSense, a plug-in sensor that generates device-level usage data for the entire home. The sensor infers the energy consumption of all appliances in the home to help owners identify how they can cut back. For example, Patel found that DVRs consume an average of 11 percent of a household’s power. The data from sensors such as Patel’s help spot energy leaks quickly and can also predict potential problems.
Netflix, with more than 36 million subscribers in the U.S. alone, would cease to function without big data. The service is powered by Hadoop, a data-processing platform that allows Netflix to allocate computing resources as the need arises. Hadoop analyzes traffic across various locations and devices to make streaming video more reliable and to strategize for the future. Hadoop is also what powers Netflix’s recommendation service that studies viewing behavior and expressed preferences.
Big data’s role in entertainment doesn’t stop there. Hollywood increasingly relies on computer-enhanced algorithms with decades of movie data to predict what will fly and what will flop. For example, analysts from Epagogix, a consulting firm for the entertainment industry, read a script and value all points of the plot, such as car chases or love scenes. They then give the script a score based on a directory. These scores are so accurate that some financiers, according to Marketplace Business, will not back a script unless the algorithms endorse it.
As we’ve already discussed in some of our recent posts, there’s a downside to all of this data aggregation, particularly when it’s combined with the aforementioned Internet of Things. As connected technology increasingly pervades every aspect of our daily lives, it’s becoming nearly inseparable from the data that these devices provide. Although the intent, ostensibly, is to make our lives easier, there’s still no escaping the fact that we are divulging an unprecedented amount of data about ourselves.
This means that unwanted information sharing will only increase, and this is a conversation that our society as a whole needs to continue revisiting. After all, the ramifications on privacy will be truly breath-taking if we allow it to grow unchecked.
In the end, it’s become very apparent that big data already is an inescapable fact of everyday life. Every time we tweet, text, search, or buy, we generate data, and that data holds enormous potential for the future. From improving healthcare delivery to protecting the nation, big data presumably means better living, but does it really mean that privacy is a thing of the past?