Overview of Big Data Research

Big Data is an emergent knowledge system that is already changing the nature of knowledge and social theory in fields such as business, health, and government while also having the power to transform management decision-making theory. It is a set of techniques, procedures, and technologies dealing with voluminous amounts of data in physical or digital formats, data that is being stored in diverse repositories, ranging from tangible account bookkeeping records of an educational institution to class test or examination records to alumni records (Sagiroglu and Sinanc 2013).

The growing interest in Big Data is associated with the sophistication of technologies used to process large and complex quantities of data and the value accrued in utilizing such data. Big Data features many characteristics, but Douglas (2001) proposed what is commonly known as the “three Vs” (volume, velocity and variety). Generally, the literature presents a number of fundamental characteristics associated with the notion of Big Data, including the following (Figure 5.1):

  • ? Volume, referring to a large amount of information that is often challenging to store, process, transfer, analyze, and present.
  • ? Velocity, relating to the increasing rate at which information flows within an organization (e.g., institutions dealing with financial information and relating that to human resources and productivity).
Key characteristics of Big Data. (From Daniel, B., British Journal of Educational Technology, 46, 5, 904-920, 2015.)

Figure 5.1 Key characteristics of Big Data. (From Daniel, B., British Journal of Educational Technology, 46, 5, 904-920, 2015.)

  • ? Veracity, referring to the biases, noise, and abnormality in data generated from various sources within an institution. It also looks at how data is stored and meaningfully mined to address problems being analyzed. Veracity also covers questions of trust and uncertainty associated with the collection, processing, and utilization of data.
  • ? Variety, referring to data presented in diverse formats, both structured and unstructured.
  • ? Verification, referring to data corroboration and security.
  • ? Value, referring to the ability of data in generating useful insights, benefits, and business processes, etc., within an institution.

There are also other important properties of Big Data, such as data validity, which refers to the accuracy of data, and data volatility, a concept associated with the longevity of data and their relevance to the outcomes of analytics, especially the length of time required to store data in a useful form for further appropriate value-added analysis.

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