Exploratory Analysis
Exploratory Data Analysis (EDA) is a critical stage in the data analysis process, enabling analysts to understand the structure, quality, and underlying patterns within a dataset before applying formal modelling techniques. By combining statistical methods and visualisation, EDA supports more informed, accurate, and reliable analysis outcomes.
Technique Overview
Exploratory Analysis Definition
Exploratory Data Analysis (EDA) is an approach to analysing datasets that focuses on summarising their main characteristics using statistical measures and visual techniques, often prior to formal modelling (Tukey, 1977). It enables analysts to identify patterns, detect anomalies, test assumptions, and gain initial insights that inform subsequent analytical steps (James et al., 2021; Wickham and Grolemund, 2017).
Exploratory Analysis Description *
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Business Evidence
Strengths, weaknesses and examples of Exploratory Analysis *
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Business Application
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Professional Tools
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Further Reading
Exploratory Analysis web and print resources *
Exploratory Analysis references (4 of up to 20) *
- Andrienko, N. and Andrienko, G., 2006. Exploratory analysis of spatial and temporal data: a systematic approach. Berlin, Heidelberg: Springer Berlin Heidelberg
- Cyril Neba C, Gerard Shu F, Nsuh, G., Philip Amouda A, Adrian Neba F, Webnda, F., Ikpe, V., Orelaja, A. and Sylla, N.A. (2024). A Comprehensive Study of Walmart Sales Predictions Using Time Series Analysis. Asian Research Journal of Mathematics, [online] 20(7), pp.9–30. doi:https://doi.org/10.9734/a
- Fayyad, U., Piatetsky-Shapiro, G. and Smyth, P. (1996). From Data Mining to Knowledge Discovery in Databases. AI Magazine, [online] 17(3), pp.37–37. doi:https://doi.org/10.1609/aimag.v17i3.12
- Ginsberg, J., Mohebbi, M.H., Patel, R.S., Brammer, L., Smolinski, M.S. and Brilliant, L. (2009). Detecting influenza epidemics using search engine query data. Nature, 457(7232), pp.1012–1014. doi:https://doi.org/10.1038/nature07634.
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