Data overload – what now?

Data overload – what now?

I’m in the middle of my second year and have recently started data collection. It’s been a surprising experience, to put it mildly. My methodology is a mixed one with short interviews, a survey and in-depth interviews. In little over a month, I have received data from more than 500 study participants (1/4 through short interviews, ¾ through the survey) and quite frankly I have felt very overwhelmed by the sheer amount of it all. Of course, before I started I was worried I wouldn’t get enough data and I was hoping for high participation rates – my methodology chapter draft has a few What if? scenarios for too little data…it doesn’t include many sections on the opposite scenario.

Being the internet-addict that I am, I googled what to do when struggling with data overload. Google didn’t really understand me though, and almost exclusively returned websites that tell you how to analyse big data. But I’ve also stumbled across a post talking about how to overcome information overload. Truth be told, it’s more about general information overload in today’s world but the symptoms I experienced seem to be the same: analysis paralysis, productivity issues, and lack of focus. Analysis paralysis because despite all that great data, I felt paralysed just thinking about it and couldn’t really fathom the thought of actually starting to get into it. Productivity issues because the moment I started transcribing one of my 128 short interviews, I felt so overwhelmed that I stopped and called it a day, and lack of focus because  in spite of my best efforts to focus on anything (not just data related) failed completely. So here I was, overwhelmed (not gonna lie, still am a bit) and not knowing how to handle it all. But I’ve had some time to let it sink in and chat to others about how they handle their data. So here are the three main initial tips I would give if you are in a similar situation:

 

(#0.    Back it up!

This has not much to do with how to handle too much data, but more with how to handle any kind of collected data: back it up! I’ve saved mine on two different devices in addition to my normal working directory. You don’t want to risk losing any of it. Imagine the nightmare…)

 

#1 Don’t panic

Despite being absolutely delighted that I managed to accumulate so much in data in a comparably short amount of time, I also felt panicky. How was I ever going to handle it all? It’s absolutely fine to feel that way. Actually, most people I talked to were a bit confused because they weren’t quite sure how a lot of data would made me panic – after all it’s great to have a lot to work with. And even though they were/are right, that just invoked panic about the panic because how could I feel this way if I clearly had it good in having so much data? However, there’s no point in denying your unease. Better to accept it and face it. The thing that helped me most was talking to my supervisors. They told me that there was no point in burning myself out over this. If I felt overwhelmed and couldn’t manage to advance in transcribing, for example, then maybe leaving it for a while was the best idea. Sometimes getting that little bit of distance is enough to calm down and gain some perspective. (I like to think of it as letting my data ripen like a good wine.)

#2 Strategy

While you ignore your data for a while, re-think your strategy. Of course, you’ve come up with a whole methodology and analysis strategy before you started collecting your data, but re-evaluate if that is still the way to go and that makes most sense. Maybe transcribing it all isn’t necessary? I’m still working on that step and it’s hard to make a decision. The most important thing seems to be to focus on what exactly it is you’re trying to find out. There’s no need to use all that data in one go. That for me is the most important point. Before, I assumed I have to use all the data I’m accumulating. But, actually, if like me you are doing inductive research and you are exploring issues, it’s likely that you have a lot of different topics emerging and a lot of different perspectives to get into. You can really only focus on one or two of those in your PhD and can leave the other ones for potential later analysis, i.e. publications. (Fun fact: it took my supervisors merely a minute to plan my whole academic career using the data I’ve collected :D)

 http://phdcomics.com/comics/archive.php?comicid=462

http://phdcomics.com/comics/archive.php?comicid=462

#3 Take a deep breath and start…

Last but not least, the day will come when you have to stop letting the data ripen and actually engage with it. For me that day came quite naturally and I just felt like looking at my data again. That is not to say that I have my whole strategy figured out yet. But what I do know is that just taking that first step is sometimes all that matters. After that, things will just start to happen. Plus, the earlier you can manage to start looking at your data, the more time you have to take it easy and just dip in and out to whatever feels most interesting to look at.

Longitudinal Research – Expectation versus reality

Longitudinal Research – Expectation versus reality

Curiosity Live at Glasgow Science Centre

Curiosity Live at Glasgow Science Centre