Abstract
The ad hoc processes of data gathering used by most organizations nowadays are proving to be inadequate in a world that is expanding with infinite information. As a consequence, users are often unable to obtain relevant information from large-scale data collections. The current practice tends to collect bulks of data that most often: (1) containing large portions of useless data; (2) leading to longer analysis time frames and thus, longer time to insights. The premise of this paper is; that big data analytics can only be successful when they are able to digest captured data and deliver valuable information. Therefore, this paper introduces ‘big data scenarios’ to the domain of data collection. It contributes to a paradigm shift of big data collection through the development of a conceptual model. In time of mass content creation, this model aids in a structured approach to gathering scenario-relevant information from various domain contexts.
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Al-Najran, N., Dahanayake, A. (2015). A Requirements Specification Framework for Big Data Collection and Capture. In: Morzy, T., Valduriez, P., Bellatreche, L. (eds) New Trends in Databases and Information Systems. ADBIS 2015. Communications in Computer and Information Science, vol 539. Springer, Cham. https://doi.org/10.1007/978-3-319-23201-0_2
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DOI: https://doi.org/10.1007/978-3-319-23201-0_2
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