Why you should break up with massive data dumps! This article is for all you data dumpers out there. You know who you are. You get all the materials for your qualitative data analysis together and you upload EVERYTHING into Dedoose…all at once. You justify these uploads by telling yourself that you are saving time later because if you need these 400 descriptor variables in the future they will be waiting for you. Then, “later” comes and you realize that you have actually wasted time uploading and sifting through massive amounts of data that you never really needed to upload in the first place.
Don’t be ashamed. You are safe with us. We too have dumped our data excessively and prematurely. At some point we just had to learn to do what was good for us. We had to break up with large data uploads. In other words, we had to dump the dumps.
Don’t make us put you in time out… When conducting mixed methods and qualitative data analysis, reducing your data dump in Dedoose can save you headaches. Of course, we understand that some qualitative data analysis projects are larger than others, so the amount of data varies from project to project. Yet, we commonly see users uploading data first, and thinking about the value of their data second. This is particularly the case when users upload large numbers of descriptor variables.
Excessively large and haphazard uploads require a strong internet connection. If your connection is not top notch, and you are in putting hundreds of cases and hundreds of descriptor fields, there is a chance that your connection might time out.
Internet connections are also known to drop their signal from time to time. If you are uploading a massive amount of data, these seemingly insignificant blips can cause major frustration because you may have to start your upload again from scratch, or will find incomplete results.
So, what is a good rule of thumb? Create an analysis plan so you can effectively reduce your data prior to upload. Decide ahead of time what questions you will focus on. Think about what data should go into your mixed methods and qualitative data analysis, and which can be excluded. There is no rule for when you need to upload the different aspects of your data. Usually it is wise to simply start by uploading the most important and informative interviews. Rather than inputting your raw statistical data in their entirety, select the descriptor variables that are most appropriate for Dedoose and most useful for your analysis. With Dedoose you can easily add more variables later if needed. To learn how to add additional descriptors to your mixed methods and qualitative data analysis when using Dedoose check out our video tutorial.
If you still don’t believe data reduction is a good idea for your qualitative data analysis, take a page from the playbook of two renowned qualitative data analysis researchers, Mathew B. Miles and A. Michael Huberman:
Data reduction is not something separate from analysis. It is part of analysis. The researcher’s decisions—which data chunks to code and which to pull out, which evolving story to tell—are all analytic choices. Data reduction is a form of analysis that sharpens, sorts, focuses, discards, and organizes data in such a way that “final” conclusions can be drawn and verified.
– Miles and Huberman, Qualitative Data Analysis: An Expanded Sourcebook (2nd ed.)
So before you upload ALL your files, think long and hard about what story you want to tell with your qualitative data analysis and mixed method data analysis. Then include the data that you will actually need. Upload the “maybe” data later. You will thank us in the end.