Introduction
My opinion is that ‘big data’ is not an appropriate term for IT professionals to use to describe different forms of structured, semi-structured, and unstructured data sets that are generated, captured, stored. Big data is defined as “data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, and does not fit into the existing database architectures” (Boyd & Crawford, 2012).
Attributes of big data
I disagree that ‘big data’ is an appropriate term used to refer to data sets beyond the ability of typical database software tools to capture, store, manage, and analyze based on the idea of the attributes of the data sets. The term used to explain the concept of storing and processing a large amount of data is not appropriate for IT professionals to use (Boyd & Crawford, 2012). Size is not an attribute that can precisely describe the meaning of the database items to an IT professional. It is argued that volume is synonymous with ‘big’ in the size of memory used to store a large amount of data (Davenport, Barth & Bean, 2013). The idea that data sets qualify to be known as ‘big data’ because the data is saved in large memory space and possesses the attributes of ‘velocity’ and ‘variety’ is ambiguous. The variables used to define the terms are inconsistent with the scientific principles of defining terms used to describe objects or events. A large amount of data that is generated, stored, retrieved, and managed using extensive software tools, does not automatically imply that the data qualifies to be described using the term ‘big data’ because the time does not tell the actual attributes of the data sets (Boyd & Crawford, 2012).
User perspectives
Again, I disagree that the term ‘big data’ is appropriate for an IT professional to use. The argument is based on the idea that different users have different perspectives on big data. To clarify the fact that the meaning of the term is ambiguous, it is essential to describe the issue from the user’s point of view (Davenport, Barth & Bean, 2013). A manager will invest money in a database designer to develop tools to manipulate data and make it meaningful to their line of work without the need to store the data on memory storage (Boyd & Crawford, 2012). The technology should support prescriptive, predictive, and retrospective data analysis techniques to suit the needs of different users. In addition to that, the academician must make a clear and precise definition of any new concept, reinforcing the position that the term ‘big data’ is not appropriate for IT professionals to use (Dewan & Kraemer, 2000).
Conclusion
In conclusion, my position is that ‘big data’ is not an appropriate term for IT professionals to use. My work is supported by two ideas, which include the ‘attributes of big data’ and the ‘user’s perspectives’ on big data. IT professionals find the term ambiguous because, according to some vendors, ‘big data’ depends on size, volume, velocity, and the inability of standard software tools to capture, store, manage and analyze a large amount of data. The perspectives of managers, scientists, and academicians do not support the use of the term ‘big data’ by IT professionals.
References
Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society, 15(5), 662-679.
Dewan, S., & Kraemer, K. L. (2000). Information technology and productivity: evidence from country-level data. Management Science, 46(4), 548-562.
Davenport, T. H., Barth, P., & Bean, R. (2013). How ‘big data is different. MIT Sloan Management Review, 54(1), 12-40