Abstract
A vast amount of complex data has been generated in every aspect of business and this enables support for decision making through information processing and knowledge extraction. The growing amount of data challenges traditional methods of data analysis and this has led to the increasing use of emerging technologies. A data-driven framework is therefore proposed in this paper as a process to look at data and derive insights in a procedural manner. Key components within the framework are data pre-processing and integration together with data modelling and business intelligence – the corresponding methods and technology are discussed and evaluated in the context of big data. Real-world examples in health informatics and marketing have been used to illustrate the application of contemporary tools – in particular using data mining and statistical techniques, machine learning algorithms and visual analytics.
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Lu, J. (2018). A Data-Driven Framework for Business Analytics in the Context of Big Data. In: Benczúr, A., et al. New Trends in Databases and Information Systems. ADBIS 2018. Communications in Computer and Information Science, vol 909. Springer, Cham. https://doi.org/10.1007/978-3-030-00063-9_32
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DOI: https://doi.org/10.1007/978-3-030-00063-9_32
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