Welcome back! We’re excited to have you with us on this data journey. To work with data, it helps to understand specific concepts—what is per capita, what is an average, how to investigate sources. These are all valuable skills and knowledge that help you navigate and understand data. What you may not realize is that the mindset you use to approach data is just as important. That’s what this post is about: how to work with data and not melt your brain. I have melted my brain many times, and it can happen no matter how great your hard skills are.
Imagine that working with data is a bit like working with electricity. Electricity is very useful and it’s all around us. At the same time, you can hurt yourself if you’re not careful. If you need to do something more involved than changing a light bulb, you should turn off the power and take off metal jewelry. Those are good habits that keep you safe. You need good habits to take care of yourself when you work with data too. Today I’m sharing four habits that I learned the hard way—by NOT doing them. Please learn from my mistakes and give them a try the next time you work with data.
Habit 1: Give yourself permission to struggle and permission to get help
A big part of my job is teaching people to work with data. At the beginning, almost everyone feels self-conscious that they aren’t “numbers people.” Every time I work with a new dataset, I have a moment where I think, “What if I just look at these data forever and they’re gibberish to me?” I have to keep reminding myself that working with data is hard. If you look at a graph and think, “I have no idea what this says,” don’t assume that it’s beyond your comprehension. Talking to other people and asking them what they think is a vital tool for me. Sometimes they understand what’s going on and can explain it to me; other times they are equally confused. Either way, that feedback is helpful. When you get stuck, remember to be patient with yourself. Think about why you’re interested in what these data say, and focus on your curiosity about them. Working with data is a skill you can learn and get better at. It’s not a test of your intelligence. When it’s hard, that’s because working with data is hard.
Habit 2: Acknowledge your feelings about the topic
It’s natural to have feelings about the world we live in, and data are a representation of our reality. Recently I did some research on suicide rates in rural Colorado, which is an important issue for libraries. I felt sad when I reviewed those data. Feelings can be even more tricky with data we collect about programs and services that directly involve us. Here at the State Library, we ask participants to complete a workshop evaluation whenever we provide training. When I get feedback that someone found my workshop useful, I am so excited. When I get feedback that they were bored, I feel bad. Check in with yourself when you’re working with data that may bring up negative feelings and take a break if you need to. Then see Habit 3.
Habit 3: Like it or not, data provide an opportunity to learn
Don’t confuse your feelings about the topic with the value of the data or the data’s accuracy. We all have beliefs and values that impact how we see the world. That’s normal. At the same time, our beliefs can make certain data hard to swallow. If the data make us feel bad, and we wish they were different, it’s easy to start looking for reasons that the data are wrong. This applies both to data that directly involve us and large-scale, community data. Remember how I said I felt bad when I got feedback that someone was bored in my presentation? I still need to review and use those data. What if I read results from a national survey that a large percentage of people think libraries are no longer valuable? I don’t feel good about that, but it’s still true that the people surveyed feel that way. Try to think of the data like the weather. You can be upset about a snowstorm in April—but that doesn’t mean it’s not snowing. You could ignore that data and go outside in shorts and sandals, but you’re the one who suffers. Better to face the data and get a coat. Data—whether you like their message or not—give you an opportunity to learn, and often to make more informed and effective decisions. Acknowledge your feelings and then embrace that opportunity.
Habit 4: Take breaks
Between trying to understand what the data say, reminding yourself you’re smart and capable, and acknowledging your feelings about the topic, you can wear yourself out quickly. It’s important to take breaks, do something else, and come back when you’re ready. Think of analyzing data like running as fast as you can. You can run really fast for short periods of time, but you can’t run that fast all day every day. Learn to notice when the quality of your thinking is starting to deteriorate. Usually I reach a point when I start to feel more frustrated and confused, and I picture my synapses in workout clothes, and they’re all out of breath and refusing to get up and run more. That’s a good signal for me that it’s time to take a break.
Learning something new is hard. Many of us received very limited training in how to work with and understand data. As you learn these strategies, keep in mind that how you approach data is just as important as the hard skills you’re learning. Take care of yourself out there and we’ll see you back here next week.
LRS’s Between a Graph and a Hard Place blog series provides strategies for looking at data with a critical eye. Every week we’ll cover a different topic. You can use these strategies with any kind of data, so while the series may be inspired by the many COVID-19 statistics being reported, the examples we’ll share will focus on other topics. To receive posts via email, please complete this form.