Qualitative research gathers information that is not in numerical form. Qualitative data is typically descriptive data and as such is harder to analyze than quantitative data
Qualitative research is useful for studies at the individual level, and to find out, in depth, the ways in which people think or feel .
Researcher can manage and organize the data by starting by developing a clear, meaningful file-naming system, such as the collection method, the date and the collector’s initials. Make this the standard for naming all qualitative data files. Then, create standard operating procedures for transforming raw data into useful information. This typically involves transcribing written data into an electronic format, categorizing and coding relevant data to find recurring themes or patterns and reviewing information to make sure it is correct. Be mindful as you go about creating schedules and setting due-dates that organizing qualitative data is often a time-consuming process .Analysis and interpretation attach significance to the information the data provides. In this step, you make sense of your results, look for underlying causes that explain results and draw conclusions. The goals are to confirm what you may already know, uncover misconceptions and identify important things that you didn’t previously know, but that you should know. For example, in analyzing results, you might confirm that communication patterns between employees and managers need improvement, discover department managers aren’t following communications protocols and that the general perception is that employees feel certain managers show favoritism.
Analysis of data requires examining, sorting, and reexamining data continually. Qualitative researchers use many means to organize, retrieve, and analyze their data. Many researchers simply use notebooks and boxes of paper. As of researcher Bogdan and Biklen (1992) describe what they call two mechanical means to organize and begin to review data. One way they describe is to write initial codes in margins of field notes, photocopy the notes and store the originals, then cut up and sort the text segments into piles according to codes. These coded data can be stored in boxes and resorted and analyzed on an ongoing basis. A second method they describe is to record field notes on pages on which each line is numbered, code the field notes, and then write the page number, line numbers, and a brief description of each piece of data on a small index card. These cards can then be sorted and analyzed. The authors note that this second method is better suited for small sets of data, as it often requires returning to the original field notes to analyze the actual data.