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Posted: May 9th, 2022
Big Data Characteristics
Big Data Characteristics
Retailers are collecting huge amount of data regarding the customers. The three characteristics of big data which includes the volume, velocity and variety apply to the collecting process of the data.
Velocity is considered as the speed of generating new data sets from the customers. It also involves the speed at which the new data is moved from one point to another. The concept is very important for the retailers to generate a large amount of data for the customers and share the data between different departments or platforms (Assunção et al, 2015). In the past computers took a longer period of processing data but currently, data is processed at high speed in terms of microseconds. The high speed of processing data ensures high quality and efficiency in the business environment. Therefore velocity is used in processing a large amount of data from the customers (Wixom et al, 2014).
The volume of big data is a large amount of data that is generated in the shortest period of time. The period should be in seconds which is appropriate in delivering the results from big data (Assunção et al, 2015). Retailers are able to generate a large volume of data within the shortest period. The characteristic is also applicable in making quick searches in large databases. The retailers are able to access a wide range of information regarding customers such as personal details, the level of purchases among others within seconds (Wixom et al, 2014). The process increases efficiency and scalability.
Variety allows the use of different data types as opposed to older processes which relied on structured data types. The structured data had a number of drawbacks with fixed tables that defined the relationships (McAfee et al, 2012). Data is now stored in various data types such as videos, images, voice among others. The retailers are able to store a large amount of data in various data types that are useful in the general operation of the business.
References
Assunção, M. D., Calheiros, R. N., Bianchi, S., Netto, M. A., & Buyya, R. (2015). Big Data computing and clouds: Trends and future directions. Journal of Parallel and Distributed Computing, 79, 3-15.
McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data: the management revolution. Harvard business review, 90(10), 60-68.
Wixom, B., Ariyachandra, T., Douglas, D. E., Goul, M., Gupta, B., Iyer, L. S., … & Turetken, O. (2014). The current state of business intelligence in academia: The arrival of big data. CAIS, 34, 1.
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