Companies all over the world are analyzing large data sets to determine patterns, trends and associations to better understand human behavior and interactions. This data collection, called “Big Data,” is revolutionizing industries and is completely altering the way we interact with online devices. While whispers of Big Data have been circulating for years, its usage has been increasing exponentially over the past few years. As its reach increases, it is only a matter of time until it infiltrates an institution like Wellesley.
People all over the world, especially college students, constantly provide information when they use online applications or programs. As Mark Zuckerberg, founder of Facebook, stated, one billion pieces of content are shared via Facebook every day. According to the data company Umbel, as each one of us enters information, we create a total of 2.5 quintillion bytes of data daily.
This information, when aggregated, helps determine patterns that better our understanding of human behavior. This better understanding can lead to breakthroughs and increases in efficiency in all industries.
One of the goals when using Big Data analytics is to gather information that will lead to insights behind customers’ behaviors and preferences. The objective is to create predictive models so that a company can better serve its customers. Therefore, by using Big Data analytics, businesses are able to optimize their processes by making predictions using social media data, web search trends and weather forecasts. For example, according to TechTarget, a technology media company, Macy’s uses Big Data to determine demand and inventory to adjust pricing in stores and online instantly for 73 million items. Similarly, by using Big Data, McKinsey predicts that a retailer could increase its operating margin by more than 60 percent, according to Umbel. Other examples include Target’s ability to accurately predict when customers are pregnant and Wal-Mart’s ability to predict what products will sell.
Likewise, politicians also use Big Data for analytics. In fact, as indicated in an LinkedIn article, many believe that a primary reason for Obama’s win in the 2012 presidential election was his campaign team’s superior ability to use Big Data.
Big Data also improves security and law enforcement. The NSA uses Big Data analytics to prevent terrorist plots, while others detect and prevent cyber attacks. In addition, by using Data Analytics, the Los Angeles and Santa Cruz police departments created an algorithm to predict where crimes are likely to occur. As a result of this algorithm, there has been a 33 percent reduction in the number of burglaries and 21 percent reduction in violent crimes in Los Angeles, according to TechTarget.
However, Big Data analytics does not only help companies and governments, but individuals as well. Since the data inputted is essentially our information, it centers on us and serves us. For example, when we use wearable devices and enter our data—data on calorie consumption and sleep patterns—the device collects it and, by combining it with data from other customers, can create personal insights and give each of us valuable advice. Such wearable devices have also been used to monitor babies that are premature or sick. By recording the babies’ heartbeats and breathing patterns, a group of doctors was able to create an algorithm that predicts whether an infection will hit 24 hours before any physical symptoms can be identified. In similar ways, but on a larger scale, Big Data can predict flu outbreaks instantly by collecting and analyzing social media data and search terms. In such a way, we can also imagine an institution like Wellesley College using Big Data to better serve its students. For example, Wellesley could track how many students eat each day in the campus center and, depending on the fluctuation of numbers, have more or less food available. This would increase efficiency and student satisfaction.
Lastly, financial trading also uses Big Data to predict and make more informed trading decisions. In fact, according to the same LinkedIn article, most equity trading currently uses algorithms that take into account data collected from social media networks and online news websites.
The Big Data trend is nowhere near flatlining—it is increasingly expanding. It is predicted that more than 15 million devices will be connected to the Internet by 2015. According to an Economic Times article, this interconnectivity will lead to an increase of big data in a wide variety of industries, such as the manufacturing, energy and transportations industries. Eventually, Big Data will not only influence the specific areas mentioned above, but all aspects of our lives.
Sabrina Leung ‘18 is the Digital Editor majoring in International Relations-Political Science with a minor in History. She is best reached at email@example.com or @sabrinatzleung on Twitter.