Excel as a Qualitative Data Analysis Tool DANIEL Z. MEYER Illinois Institute of Technology LEANNE M. AVERY State University of New York College at Oneonta Qualitative research seeks to examine the interconnections in rich, complex data sources. The statistical tools of quantitative methods separate out pieces of data in a manner that defeats the purpose. But, like quantitative researchers, qualitative researchers often still find themselves overwhelmed by the amount of data and equally in need of tools to extend their human senses. This has led the development of a number of software packages designed for this purpose. An often overlooked option, however, is Microsoft Excel. Excel is generally considered a number cruncher. However, its structure and data manipulation and display features can be utilized for qualitative analysis. In this article, the authors discuss data preparation, analysis, and presentation, including discussion of lesser known features of Excel. Keywords: qualitative methods; data analysis; constant comparative method Researchers using qualitative data often find themselves lost in a sea of data. Although it is the very richness and interconnectiveness that we find appealing, the data can also be overwhelming. Some sense must be made of them while preserving their complexity. We therefore conceptualize tracking as a central hurdle in qualitative data analysis: We often need to be able to connect one bit of qualitative data to another bit. This need to track has resulted in a significant market for qualitative data analysis software tools that utilize the power of modern computing to augment our own human senses. Excel is often viewed as a number cruncher and is therefore associated with quantitative data analysis, but we have also found it useful as a quali- tative tool. It can handle large amounts of data, provide multiple attributes, and allow for a variety of display techniques. In this article, we demonstrate the use of Excel as a qualitative data analysis tool. We will cover data preparation, analysis, and presentation, paying particular attention to less 91 Field Methods, Vol. 21, No. 1, February 2009 91–112 DOI: 10.1177/1525822X08323985 © 2009 Sage Publications at SAGE Publications on June 26, 2015 fmx.sagepub.com Downloaded from