Requirements of Data Visualisation Tools to Analyse Big Data: A Structured Literature Review

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Abstract

The continual growth of big data necessitates efficient ways of analysing these large datasets. Data visualisation and visual analytics has been identified as a key tool in big data analysis because they draw on the human visual and cognitive capabilities to analyse data quickly, intuitively and interactively. However, current visualisation tools and visual analytical systems fall short of providing a seamless user experience and several improvements could be made to current commercially available visualisation tools. By conducting a systematic literature review, requirements of visualisation tools were identified and categorised into six groups: dimensionality reduction, data reduction, scalability and readability, interactivity, fast retrieval of results, and user assistance. The most common themes found in the literature were dimensionality reduction and interactive data exploration.

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Lowe, J., & Matthee, M. (2020). Requirements of Data Visualisation Tools to Analyse Big Data: A Structured Literature Review. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12066 LNCS, pp. 469–480). Springer. https://doi.org/10.1007/978-3-030-44999-5_39

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