 The perils of working with big data, and a SMALL checklist you can use to recognize themScott Brave, R. Andrew Butters and Michael Fogarty Business Horizons, 2022, vol. 65, issue 4, 481-492 Abstract: The use of big data to help explain fluctuations in the broader economy and key business performance indicators is now so commonplace that in some instances it has even begun to rival more traditional measures. Big data sources can very often provide advantages when compared with these more traditional data sources, but with these advantages also come potential pitfalls. We lay out a checklist called SMALL that we have developed in order to help interested parties as they navigate the big data minefield. Based on a set of five questions, the SMALL checklist should help users of big data draw justifiable conclusions and avoid making mistakes in matters of interpretation. To demonstrate, we provide several case studies that demonstrate the subtle nuances of several of these new big data sets and show how the problems they face often closely relate to age-old concerns that more traditional data sources are also forced to tackle. Keywords: Big data; Data analysis; Economic forecasting; Selection bias; Reporting lags; High-frequency data; Real-time forecasts; Leading indicator (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:bushor:v:65:y:2022:i:4:p:481-492 DOI: 10.1016/j.bushor.2021.06.004 Access Statistics for this article Business Horizons is currently edited by C. M. Dalton More articles in Business Horizons from Elsevier |
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