Following a brief review of the problematic nature of open-ended questions in survey analysis the paper then characterizes the nature of coding and data analysis in qualitative research. While a common thread between survey and qualitative research is that data analysis is fundamentally a process of data reduction, the variety of approaches to qualitative data analysis obliges those who pursue a systematic practice of qualitative research to provide an 'audit trail' of analytic decisions. This customarily involves field diaries, coding commentaries and analytic memos, but the emergence of qualitative software (generically, 'CAQDAS') has brought digital resources to the task. The paper will profile computational affordances at the stages of data entry and coding, data analysis (highlighting Boolean retrieval strategies), and validation (highlighting system closure, Artificial Intelligence routines, and data integration). The role of developments in data archiving and secondary analysis in the drive for formal, systematic analysis will be outlined, and the conclusion will consider the disambiguation issue in content analysis and the possible susceptibility of open coding problems to Boolean and/or Artificial Intelligence solutions.