Big Data
What is Big Data?
- Doug Laney
In 2001, the term “big data” struck the IT industry and has since become a mainstream influence on all businesses. Analyst Doug Laney of Gartner Research, who has currently dedicated 28 years to the industry, coined the term when referencing “exponential growth and availability of data” (Davenport and Dyche, 2013). According to Laney, there are three parts of the big data definition: the three Vs, cost-effective information processing, and enhanced insight and decision making (Sicular, 2013). Variety, velocity, and volume are considered the dynamic trio of big data quantification. Part two of the big data definition, cost-effective information processing, references the affordable technology used to store and process unstructured data. Finally, enhanced insight and decision making is labeled as the “ultimate goal,” according to Forbes, and creates business value through greater insights and a growth of analytic skills. The combination of these three dimensions is the underlying factor that creates big data.
How does Big Data relate to MIS2502?
Big data strongly correlates with MIS2502, or Data Analytics, and builds on the material covered throughout the duration of the course. One key concept of the course is that data can be extracted and manipulated in numerous ways to provide valuable knowledge for companies. The purpose of data analytics is to provide analyses to make business decisions and have confidence in the results – big data offers just that, but with more accuracy due to the vast amount of data being evaluated. Big data elaborates on the ability to discover trends in analytical data stores using the data mining techniques that MIS2502 covers like clustering, segmentation, and association. Big data and the MIS2502 course material work together in many ways to create an advanced understanding of data usage in the business world.
How has Big Data been applied?
Big data has become popular over the past decade because it provides valuable analytical knowledge for businesses of all kinds and consistently offers positive results. It teaches analysts how to take large data sets and turn them into information that allows the company to enable cost reductions, new product development, and more. For example, companies like UPS have taken full advantage of big data by implementing telematics sensors in more than 46,000 vehicles in an attempt to reconfigure driver pickups and drop-offs. This initiative, called ORION (On-Road Integration Optimization and Navigation) has led to a decrease of more than 8.4 million gallons of fuel by cutting 85 million miles off of daily routes (Davenport and Dyche, 2013). UPS is just one company that has seen substantial benefits from the use of big data and I am certain they will continue to use it to make tactical business decisions in the future.
References
Davenport, Thomas H., and Dyche, Jill. “Big Data – What It Is & Why It Matters.” SAS, May 2013. Web. 23 Apr. 2015.
Sicular, Svetlana. “Gartner’s Big Data Definition Consists of Three Parts, Not to Be Confused with Three “V”s.” Forbes. Forbes Magazine, 23 Apr. 2015. Web. 27 Mar. 2013.