by Erin S
Every day 2.5 quintillion bytes of data are created and 90 percent of the data in the world today were produced within the past two years. Because the amount of data is growing and at such a large rate, the challenges of handling this data with the intention to use and to apply it using tools such as data mining has become more and more complex, and has caused a constant need to scale up to the large volume of data that must be interpreted. With this large influx of new data and information comes many new opportunities to use and to apply data mining. This most often seems to apply in a business sense, used in order to “improve customer service, better target marketing campaigns, identify high-risk clients, and improve production processes” or in other words to make money, such as when Walmart learned that people have a tendency to buy more Pop Tarts when there was a hurricane warning in the affected area and instructed store managers to place Pop Tarts near the entrance during hurricane season in order to boost sales. Other companies such as Facebook and Twitter make use of this data by selling it to other companies who then apply data mining better market their products by finding new customers or by better targeting their products to existing ones. However, data mining isn’t only useful to businesses. It can also affect different aspects of a person’s everyday life.
One example of this is a new app called Qloo. Qloo is sort of a “personalization engine.” It allows a person to enter the movies, music, books, TV shows, restaurants, bars, travel destinations or fashion brands that they like and will then start to make recommendations in these various categories. Qloo uses an algorithm that tags similarities among various items and makes recommendations based on these similarities. However, because Qloo seems to be in its beginning stages and targets a much larger range of interests, the associations used to make these recommendations tend to be weak and often inaccurate. One example that the writer in the article brought up was how he was prompted the suggestion for “The Joy of Cooking,” which he determined could only possibly be attributed to his love of the cartoon “Bob’s Burgers.” Qloo also allows users to follow one another and to see those who display similar tastes as their own.
However there are many other services other than Qloo that also utilize data mining to provide user recommendations, which tend to be much more accurate, as they focus more on a certain niche rather than trying to group all the different aspects of a person’s life together and provide suggestions based on such. One example of a more specific service that utilizes data mining and is also incredibly popular is Netflix. Netflix provides is users with different recommendations on what they might like to watch based on data involving what users watch, what they search for and what they rate, as well as the time of day, the date, and what device they use to view it on. This complex system of analyzing data and providing suggestions has led to more than 75% of Netflix’s user activity being driven by recommendations. Netflix can also use this information to predict what kind of content it should buy or produce for its users in the future.
GoodReads is another popular service that applies databases. GoodReads is an online book recommendation engine. It applies a set of algorithms which look at over 20 billion different data points, taking into account the preferences of its nearly 6 million users, as well as the rating system that is a key component to the function of this site. Because the rating system is so key, each person is encouraged to rate at least 20 books before viewing their suggested reading list. The site then is able to separate their different recommendations based by genre. Then, going even further, the user is also allowed to create certain shelves based on personal preferences and GoodReads will take these shelves and make even more recommendations based on their contents. Furthermore, GoodReads acts as a social network and allows its users to friend and follow other friends, authors, and people as well as view what they read, how they rated their books, and compare all this to their own books and ratings.
Other online services that make use of data mining include Pandora Radio, which provides its users with suggestions based on their music preferences and StumbleUpon which recommends its users different websites, photos and videos based on personal preferences and ratings.
Overall, while it may seem like big data and data mining are only important to big businesses and those looking to make a profit, databases still affect people on a more personal level and can help to improve different aspects of their everyday lives.
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