Which of the Following Best Describes Big Data?
Which of the following best describes big data? According to those who understand its definition and study it, the term refers to the method of gathering massive amounts of information about virtually any aspect of human behavior. In essence, the system allows researchers to” map” the human brain in order to detect patterns and relationships that existed before the person’s existence. The result is then used to predict and identify new tendencies or behaviors that emerge.
Although this appears to be a new discovery, the process has been in use for decades. For instance, researchers had already been in the field of psychology for decades before computer scientists came up with the term. Still, many in the scientific community still do not fully appreciate how big data can help their research findings. Still, others believe that as technology becomes more adept at collecting and using large amounts of data, psychologists will eventually use it for studying all aspects of social life. Whether or not this is true remains to be seen.
Perhaps the first aspect of data that needs to be examined is its definition. According to dictionaries and thesauruses, the word data can mean a collection of data, especially with reference to organized and accounting practices. It can also refer to the results obtained from experiments, surveys, or studies. In computer parlance, data are computer software or information that is prepared for presentation, analysis, etc. The new phenomenon of big data may be summarized by the term social networks.
Social networks are online networks in which people interact with each other on a regular basis. The interaction can take many forms, but typically it involves forming relationships. On such networks, people share information about their personal lives, their interests, politics, religion, sex, work, education, friends, and so on. The extent to which an individual interacts with others in these online environments is growing, as evidenced by the existence of MySpace, Facebook, and Twitter. In a broader sense, networks can also refer to internet communities, online newspapers, television and radio shows, and news websites.
The biggest challenge for marketers is how to extract value from big data in terms of finding a way to make money with it. Some have already done this using sites such as Google’s AdSense. Others are in the process of doing so on a more sophisticated scale using sites like Yelp and Foursquare. There is even some buzz in the marketing world about using data from social networks to predict consumer behavior.
Because these networks are inherently rich, one can expect that their information will have several uses beyond being used by marketers. For example, by using Twitter to follow users who post tweets about the latest trends, a marketer can learn which topics to keep the interest of the public. By studying the relationships between people in the networks, one can learn which topics resonate with the people most, which groups are the most cohesive, and which groups are the most volatile. Being able to predict where the interest is likely to be gives a marketer a leg up on the competition.
This type of predictive technology is very important for companies who are trying to understand customer behavior. By being able to predict what types of conversations a customer is likely to have, a marketer can craft campaigns based on this information. Marketers are already leveraging this type of technology to improve sales by helping customers decide what products they might want to buy based on conversations they’ve had with friends and family. Using big data to improve a company’s bottom line gives it a unique advantage over its competitors.
Which of the following best describes big data? It’s complicated. But then again, it isn’t so difficult that it isn’t exciting. It provides a new framework for understanding consumer behavior that helps a marketer decide what messages to deliver to customers, which types of events to attend to gain their attention, and which kinds of products to offer that will appeal to them. With the right tools, it can be used to provide results that are much more effective than any traditional analysis.