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The perils of working with big data, and a SMALL checklist you can use to recognize them

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  • Brave, Scott A.
  • Butters, R. Andrew
  • Fogarty, Michael

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.

Suggested Citation

  • Brave, Scott A. & Butters, R. Andrew & Fogarty, Michael, 2022. "The perils of working with big data, and a SMALL checklist you can use to recognize them," Business Horizons, Elsevier, vol. 65(4), pages 481-492.
  • Handle: RePEc:eee:bushor:v:65:y:2022:i:4:p:481-492
    DOI: 10.1016/j.bushor.2021.06.004
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    as
    1. Tucker McElroy, 2017. "Multivariate Seasonal Adjustment, Economic Identities, and Seasonal Taxonomy," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 611-625, October.
    2. Alharthi, Abdulkhaliq & Krotov, Vlad & Bowman, Michael, 2017. "Addressing barriers to big data," Business Horizons, Elsevier, vol. 60(3), pages 285-292.
    3. Crane, Leland D. & Decker, Ryan A. & Flaaen, Aaron & Hamins-Puertolas, Adrian & Kurz, Christopher, 2022. "Business exit during the COVID-19 pandemic: Non-traditional measures in historical context," Journal of Macroeconomics, Elsevier, vol. 72(C).
    4. Earley, Christine E., 2015. "Data analytics in auditing: Opportunities and challenges," Business Horizons, Elsevier, vol. 58(5), pages 493-500.
    5. Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 151-178, Spring.
    6. Alberto Cavallo, 2017. "Are Online and Offline Prices Similar? Evidence from Large Multi-channel Retailers," American Economic Review, American Economic Association, vol. 107(1), pages 283-303, January.
    7. Pierre Azoulay & Joshua S Graff Zivin & Danielle Li & Bhaven N Sampat, 2019. "Public R&D Investments and Private-sector Patenting: Evidence from NIH Funding Rules," Review of Economic Studies, Oxford University Press, vol. 86(1), pages 117-152.
    8. Susan Herbst-Murphy, 2013. "Clearing and settlement of interbank card transactions: a MasterCard tutorial for Federal Reserve payments analysts," Consumer Finance Institute discussion papers 13-02, Federal Reserve Bank of Philadelphia.
    9. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    10. Lee, In, 2017. "Big data: Dimensions, evolution, impacts, and challenges," Business Horizons, Elsevier, vol. 60(3), pages 293-303.
    11. Menelik Geremew & François Gourio, 2018. "Seasonal and Business Cycles of U.S. Employment," Economic Perspectives, Federal Reserve Bank of Chicago, issue 3, pages 1-28.
    12. Alexander W. Bartik & Marianne Bertrand & Feng Lin & Jesse Rothstein & Matthew Unrath, 2020. "Measuring the Labor Market at the Onset of the COVID-19 Crisis," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(2 (Summer), pages 239-268;316.
    13. Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz & Tyler Radler, 2018. "Using Payroll Processor Microdata to Measure Aggregate Labor Market Activity," Finance and Economics Discussion Series 2018-005, Board of Governors of the Federal Reserve System (U.S.).
    14. Judith A. Chevalier & Anil K. Kashyap & Peter E. Rossi, 2003. "Why Don't Prices Rise During Periods of Peak Demand? Evidence from Scanner Data," American Economic Review, American Economic Association, vol. 93(1), pages 15-37, March.
    15. Nagle, Tadhg & Redman, Tom & Sammon, David, 2020. "Assessing data quality: A managerial call to action," Business Horizons, Elsevier, vol. 63(3), pages 325-337.
    16. Walker, Russell, 2015. "From Big Data to Big Profits: Success with Data and Analytics," OUP Catalogue, Oxford University Press, number 9780199378326, Decembrie.
    17. Tyler Atkinson & Jim Dolmas & Christoffer Koch & Evan F. Koenig & Karel Mertens & Anthony Murphy & Kei-Mu Yi, 2020. "Mobility and Engagement Following the SARS-Cov-2 Outbreak," Working Papers 2014, Federal Reserve Bank of Dallas.
    18. Sumedha Gupta & Thuy D. Nguyen & Felipe Lozano Rojas & Shyam Raman & Byungkyu Lee & Ana Bento & Kosali I. Simon & Coady Wing, 2020. "Tracking Public and Private Responses to the COVID-19 Epidemic: Evidence from State and Local Government Actions," NBER Working Papers 27027, National Bureau of Economic Research, Inc.
    19. Barsky, Robert B & Miron, Jeffrey A, 1989. "The Seasonal Cycle and the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 97(3), pages 503-534, June.
    20. Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2020. "Tracking Labor Market Developments during the COVID-19 Pandemic: A Preliminary Assessment," Finance and Economics Discussion Series 2020-030, Board of Governors of the Federal Reserve System (U.S.).
    21. Aditya Aladangady & Shifrah Aron-Dine & Wendy Dunn & Laura Feiveson & Paul Lengermann & Claudia Sahm, 2021. "From Transaction Data to Economic Statistics: Constructing Real-Time, High-Frequency, Geographic Measures of Consumer Spending," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 115-145, National Bureau of Economic Research, Inc.
    22. Pham, Xuan & Stack, Martin, 2018. "How data analytics is transforming agriculture," Business Horizons, Elsevier, vol. 61(1), pages 125-133.
    23. R. Andrew Butters, 2020. "Demand Volatility, Adjustment Costs, and Productivity: An Examination of Capacity Utilization in Hotels and Airlines," American Economic Journal: Microeconomics, American Economic Association, vol. 12(4), pages 1-44, November.
    24. Jaap H. Abbring & Jeffrey R. Campbell, 2005. "A Firm's First Year," Tinbergen Institute Discussion Papers 05-046/3, Tinbergen Institute.
    25. Jose Maria Barrero & Nick Bloom & Steven J. Davis, 2020. "60 Million Fewer Commuting Hours Per Day: How Americans Use Time Saved by Working from Home," Working Papers 2020-132, Becker Friedman Institute for Research In Economics.
    26. Vanhoof Maarten & Reis Fernando & Ploetz Thomas & Smoreda Zbigniew, 2018. "Assessing the Quality of Home Detection from Mobile Phone Data for Official Statistics," Journal of Official Statistics, Sciendo, vol. 34(4), pages 935-960, December.
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