The process of data collection can be described as a tedious, time consuming and repetitive exercise. This is especially the case when the data collected focuses on a selected sample, in a selected location, targeting a sample size that has the same characteristics, thus creating avenues where the queries may tend to generate similar responses (Denzin & Lincon, 2005). This is what has been described and defined as saturation of data during the process of research. The major disadvantage of a saturated data collection process is the fact that absolutely no new data or information is attained in the overall process of data collection. This creates an avenue of redundancy and repetition. The researcher is then tasked with the mandate of using the collected information, filling in the gaps of the research processes with the same amount of data collected from the respondents.
In qualitative research on information systems by Michael D. Myers, the author notes of the herculean task involved during data collection. The field of information systems is ever changing and evolving (Myers, 1997). During the process of data collection, interviews, questionnaires, observation and analysis was used. The sample targeted projected similar responses from the people in the field of IS. This was a direct result of the current IS trends, aspects, observations and processes which tend to be the same all over. The author states that IS processes tend to cover the range and spectrum of issues in the field. In conclusion, the sole purpose of research is to bring out new information and data that can generally help the field that has necessitated the topic of research. As a result, the saturation of data is a great set back in any research (Myers, 1997).
References
Denzin, N. K., & Lincoln, Y. S. (2005). The Sage Handbook of Qualitative Research. California: Sage Publishers.
Myers, M. D. (1997). Qualitative research in information systems. MISQ Discovery.
