What Is the Future of Big Data?

¶ … Big data: What does it mean for your business?

Once data about consumers was relatively difficult to amass. Now, in the digital age businesses are assaulted with a plethora of sources of consumer data. "Data now stream from daily life: from phones and credit cards and televisions and computers; from the infrastructure of cities; from sensor-equipped buildings, trains, buses, planes, bridges, and factories. The data flow so fast that the total accumulation of the past two years -- a zettabyte -- dwarfs the prior record of human civilization" (Shaw 2014). The big data revolution has the power to be as revolutionary as the Internet in the ways that businesses conduct commerce and consumers view themselves. "Big data is distinct from the Internet, although the Web makes it much easier to collect and share data. Big data is about more than just communication: the idea is that we can learn from a large body of information things that we could not comprehend when we used only smaller amounts" (Cukier & Schoenberger 2013).

In the past small samplings of large populations were used to make sweeping generalizations. However, big data allows for the creation of unexpected connections: "Big data is also characterized by the ability to render into data many aspects of the world that have never been quantified before; call it 'datafication.' For example, location has been datafied, first with the invention of longitude and latitude, and more recently with GPS satellite systems. Words are treated as data when computers mine centuries' worth of books. Even friendships and 'likes' are datafied, via Facebook" (Cukier & Schoenberger 2013). The greater the ease of data analysis, the greater the likelihood of 'datafacation' in our daily lives will penetrate more and more unexpected spheres.

Big data may be contrasted with 'small data' or the use of consumer data bases. These databases make use of 'sampling. "Modern sampling is based on the idea that, within a certain margin of error, one can infer something about the total population from a small subset, as long the sample is chosen at random…it falls apart when we want to drill down into subgroups within the sample," say, of gay males under 30 with incomes of more than $30,000 (Cukier & Schoenberger 2013). Then, "the random sample is largely useless, since there may be only a couple of people with those characteristics in the sample, too few to make a meaningful assessment of how the entire subpopulation will vote" (Cukier & Schoenberger 2013). However, if the sampling is the entire population of consumers, in other words, if it is sufficiently 'big' then the problem disappears (Cukier & Schoenberger 2013).

Big data is thus not just a trend or a catchword, but a new source of information for businesses to more accurately segment and target customers. The greater accuracy and complexity of big data also gives an advantage to companies with the money and resources to obtain large data samplings. Even large customer databases do not allow for the types of correlations provided by Big Data. "Datafication is a far broader activity: taking all aspects of life and turning them into data. Google's augmented-reality glasses datafy the gaze. Twitter datafies stray thoughts. LinkedIn datafies professional networks" (Cukier & Schoenberger 2013). Unlike asking consumers directly about their buying habits or creating correlations between direct purchases and consumer behavior, big data can even mine unintentional clues that people give about themselves. Once upon a time, a small company could 'get away' with simply doing customer satisfaction surveys of those customers who frequently used the product and were loyal shoppers -- such an attitude is now largely relegated to the past.

Big data is also not just confined to the business sphere. Some people consider big data a mindset and a philosophy just as much as it is an analysis technique. "There is a movement of quantification rumbling across fields in academia and science, industry and government and nonprofits…Half the members of the government department are doing some type of data analysis, along with much of the sociology department and a good fraction of economics" (Smith 2014). Big data as a concept thus has penetrated a wide variety of areas and will likely continue to affect the ways in which academics conceive of how human beings behave. There is dialogue between the marketplace of ideas and the academic world and the relationship between the two is only likely to grow and solidify as higher-level quantitative analysis grows ubiquitous in business.

Big data has proven to be profitable for companies "such as Netflix and Amazon to make purchase suggestions based on the prior interests of one customer as compared to millions of others" and can help companies sift through large amounts of information (Smith 2014). "Target famously (or infamously) used an algorithm to detect when women were pregnant by tracking purchases of items such as unscented lotions -- and offered special discounts and coupons to those valuable patrons" (Smith 2014). This can increase customer loyalty in a relatively unobtrusive fashion: customers feel pleased that they are being offered discounts on products they find useful without being aware of how and why they are being segmented in such as targeted fashion. Even credit-card companies "have found unusual associations in the course of mining data to evaluate the risk of default: people who buy anti-scuff pads for their furniture, for example, are highly likely to make their payments" (Smith 2014). This can enable companies to engage in a more effective technique of risk management than simply looking at a credit score: big data clues may give a more accurate analysis of where the particular consumer is 'trending' in his or her life than a score based upon past data, because big data is grounded in the present, for the most part. Customer relationship managers have more sophisticated tools to process and analyze information about customers and more skillfully tailor customer relationship policies to the customer's present needs