Big Data
Big Data
Big data is a common saying that is used today but most people cannot define what it means. Many people know that big data includes a large amount of information gathered but it is a mystery on what they do with the information and how it can be useful. The article “What Is Big Data? A Consensual Definition and a Review of Key Research Topics” attempts to define big data. It says, “Big Data represents the Information assets characterized by such a High Volume, Velocity and Variety to require specific Technology and Analytical Methods for its transformation into Value” (Mauro 103). There are three main parts to this definition. Volume, velocity and variety are used to describe the characteristics of the information involved (Mauro 103). Technology and analytical methods are required in order to handle the large amount of information and make it useful (Mauro 103). From the technology and analytical methods, the information is transformed into economic value so business can benefit from it (Mauro 103). The topic of big data can be very broad hence it has a broad definition.
Big data can have a huge impact on our lives because it can give us important insight that we were not able to see before. For example, analysis of google searches from people have been used to forecast unemployment, inflation and even an influenza epidemic (Mauro 100). Big data can also have a negative impact on society. This negative impact includes privacy concerns, ethical issues of protecting free will from the prediction power that big data gives us, and the power given to people with exclusive control over data (Mauro 100). The ability to harness big data can be a huge competitive advantage for society and business.
The topic of big data builds on concepts from MIS 2502 because the central part of big data is data analytics. In order to gain a competitive advantage form big data, it has to be cleaned and analyzed into something useful. During MIS 2502, we learned a lot about storing, cleaning, and analyzing data through various programs and methods. Big data relates to the topics of relational data modeling, SQL, semi-structured data, NoSQL, ETL (Extract, Transform, and Load), Advanced Analytics, and R. The central part of big data is data analytics so a lot of topics covered in MIS 2502 can be directly related.
Big Data has been used to help improve airline ETAs (Estimated time of arrival). For example, a major U.S. airline discovered that 10% of flights into their major hub had a 10-minute gap between the ETA and the actual time of arrival (McAfee 6). They also figured out that 30% of flights had a gap of at least 5 minutes (McAfee 6). The airline wanted to eliminate these gaps because it was wasting them money, so they found a better solution. They were originally relaying on the pilot to give the ETA but then they discovered PASSUR (McAfee 6). PASSUR provided them with a system called RightETA (McAfee 6). It calculated ETAs by using past data from flights to accurately give a correct arrival time, which saved the airline millions (McAfee 6). Currently most big airlines relay on big data to accurately predict ETAs.
Works Cited
Mauro, Andrea De, et al. “What Is Big Data? A Consensual Definition and a Review of Key Research Topics.” Jour, 9 Feb. 2015, doi:10.1063/1.4907823.
McAfee, Andrew, and Erik Brynjolfsson. “Big Data: The Management Revolution.” Harvard Business Review, Harvard Business Review , 8 Oct. 2014, hbr.org/2012/10/big-data-the-management-revolution.