To protect your work, get in the habit of making regular back-ups.Explore your material and code themes as they emerge-create memos and describe your discoveries and interpretations.Set up cases for the people, places or other cases in your project.Set up an initial node structure based on your early reading and ideas-you could run a Word Frequency query over your data to tease out the common themes for creating your node structure.Import your interviews, field notes, focus groups -organize these files into folders for easy access.Show the relationships or patterns you expect to find in your data based on prior experience or preliminary reading. Make a mind map for your preliminary ideas.Why are you doing the project? What is it about? What do you expect to find and why? Make a project journal and state your research questions and record your goals.Import your research design, grant application or thesis proposal. Start now - don't wait until you have collected all the data.Since projects (and researchers) are unique there is no one 'best practice' approach to organizing and analyzing your data but there are some useful strategies to help you get up and running: As part of the import, choose to run automated insights to identify and code at themes and sentiment so that you can quickly review results and report broad findings. You would import it using the Survey Import Wizard, which prepares your data for analysis. Your file is a large dataset of survey responses. Feel free to share your own ideas and strategies on the QSR Forum. This page presents some example scenarios for handling different types of projects-these are just suggestions to get you up and running. How do I choose the best approach for my project?Įvery research project is unique-the way you organize and analyze the material depends on your methodology, data and research design. For example, this picture shows a path you might take to investigate an interesting theme: Instead, it tends to be an iterative process where you explore, code, reflect, memo, code some more, query and so on. Handling qualitative data is not usually a step-by-step process.

Qualitative research as an iterative process NVivo can help you to manage, explore and find patterns in your data but it cannot replace your analytical expertise. NVivo doesn’t favor a particular methodology-it’s designed to facilitate common qualitative techniques no matter what method you use. A researcher looking for ways to improve health policy or program design might use ‘evaluation methods’. For example, a social scientist wanting to develop new concepts or theories may take a ‘grounded theory’ approach. Researchers usually adopt a qualitative methodology to suit their research question. They analyze data like interviews, surveys, field notes, web pages, audio visual material and journal articles. Qualitative researchers are interested in evaluating, interpreting and explaining social phenomena.

Using nvivo