Big data refers to the exponential growth, availability, and use of information whose data sets are too large for commonly used software tools to analyze efficiently. Only 10% of big data is structured, meaning it is stored in databases, while 90% of big data is unstructured. Unstructured data consists of “human information” such as emails, videos, tweets, Facebook posts, etc. Big data is important because organizations and IT leaders need to focus on the increasing volume, variety, and velocity of information that is being created each day. We create 2.2 million terrabytes of data daily, which means organizations must be constantly analyzing and storing new data.
Big data relates to much of the material covered in MIS 2502 because big data refers to the continuing growth of information and the need to quickly analyze this data and in class we learned about the importance of storing and analyzing data. In MIS 2502 we learned that data is discrete, unorganized, raw facts, while information is the transformation of these facts into meaning. Big data is so large that it is very difficult to transform this data into information, and it is too costly for companies to store it in relational databases like SQL, which we used in class. Data mining is more appropriate when analyzing big data because it allows companies to focus on specific pieces of information.
The retail industry has recently implemented big data analytics with compelling results. Macy’s now analyzes tens of millions of terabytes of information every day, including store transactions and social media. Their switch to big data analytics resulted in a 10% increase in sales. For retail stores such as Sears and Target, big data helps them by analyzing behavior patterns resulting in greater sales, predict in-store sales based on weather patterns, and signal hot products. All of this analysis is being executed in real-time rather than weeks or months later, allowing the retail stores to react quickly to changes and improve sales faster. Big data is the way of the future and if other stores want to keep up with Macy’s, Sears, and Target, big data analytics is a necessity.
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Gustke, Constance. “Retail Goes Shopping Through Big Data.” CNBC.com. N.p., 15 Apr. 2013. Web. 27 Apr. 2013. <http://www.cnbc.com/id/100638141>.
“What Is Big Data?” Autonomy, n.d. Web. 27 Apr. 2013. <http://www.autonomy.com/content/Technology/what-is-big-data/index.en.html>.
“What Is Big Data?” IBM, n.d. Web. 27 Apr. 2013. <http://www-01.ibm.com/software/data/bigdata/>.