Qualitative data analysis (QDA) is the process of searching for patterns and themes in large volumes of unstructured data to help answer relevant research questions. This research approach commonly uses computer software, known as QDA software, to search for these connections.
Here are some common examples of qualitative data:
QDA software can be a great asset to your research project and will allow you to effectively transform and analyze unstructured data.
QDA software assists with organizing, annotating, searching and displaying your data. You can import your data into QDA software so all of your data exists in one location and is directly linked to all project files. There are a variety of qualitative techniques supported by QDA software, such as:
Please note that QDA software is not able to analyze your data, but rather is a tool for engaging with data. Plan to use QDA software as a way to organize and access information about your data more quickly and easily to assist with analysis.
“The central analytic task in qualitative research — understanding the meaning of text — cannot be computerized” (Kelle, 1995).
To learn more, watch this video: What Qualitative Data Analysis software can and can’t do for you.
The best software for your project depends entirely on your unique project’s needs.
If you’re planning on using QDA software, first consider your research question and envision what you expect to learn from your analysis. This will help you determine what methods and software best meet your project’s goals.
Here are some important questions to consider:
Answering these questions early on in the research process will help you develop a methodology and select the best software for your research aims. Ultimately, this will save you time and effort in completing your qualitative data analysis.
To learn more, watch this video: Choosing Qualitative Data Analysis Software: Qualitative Research Methods
Each QDA software offers different features and has strengths and weaknesses depending on your project’s goals.
Please check out these detailed descriptions and comparisons of popular QDA software options:
| Software | Availability for SESYNC Community |
Open Source |
|---|---|---|
| NVivo | Yes | No |
| MAXQDA | Yes | No |
| ATLAS.ti | No | No |
| Dedoose | No | No |
| R QDA Packages: qcoder, Aquad, RQDA, TM (Text Mining), Network, Tidytext |
Yes | Yes |
| Python QDA Packages: PyQDA, QualCoder |
Yes | Yes |
| Weft QDA | Yes | Yes |
| Taguette | Yes | Yes |
In addition to those listed above, there are a many free and open-source QDA platforms. These options tend to have more basic functionality, giving you the opportunity to explore what features you need and don’t need, before deciding to invest time and funds in more sophisticated software.
Some of these options make use of R and Python. If you have experience coding on these platforms this may be a good time saving option. Check out SESYNC’s lesson on using R to Structure for Unstructured Data.
Lastly, many proprietary QDA software options offer a free trial. Use this as an opportunity to explore how the software displays, organizes and exports your data to decide which software is the right fit.
If you would like to discuss using QDA software, or are interested in using a software option that is not currently available at SESYNC, please contact cyberhelp@sesync.org.