Top 3 Non-Technical Skills for Effective Data Analyst
Data analytics is a highly technical field. As someone still new on this career path, I spend a lot of my time focusing on learning and improving my technical skills. However, I recognize that to thrive in a work environment and be an effective data analyst, developing and honing non-technical skills, aka soft skills, are just as important.
So, in this blog, I’ll share what I think are the top 3 non-technical skills needed to be an effective data analyst. Even though I’m penning this, I do not claim to excel in these skills. I’m working on improving these myself. I’m a big believer in continuous improvement, and therefore there is no destination to this process.
1. Communication
A big bulk of our work is digging through raw data and trying to make sense of and derive meaning from it. However, it doesn’t help anyone if we lack the communication skills to deliver it to the intended audience in a way that’s easy to comprehend. Often, our audiences aren’t our immediate analytic colleagues but people in management and leadership positions. Not many of these folks are interested to hear the technical stuff like RMSE or R2 on the forecast (for those wondering, both are measures of goodness of fit of a model). They have different priorities and not a lot of time. Colleagues outside the analytics team speak a different language; they speak business language, so to be a successful analyst, we need to be bilingual and analytics translators.
As an analyst, it is not uncommon that we are required to report our conclusion in a group setting, so get comfortable and good at public speaking and presentation. Many people have glossophobia, a fear of public speaking, “it is believed to affect up to 75% of the population…” (Psycom, Glossophobia). I’m one of the 75% of the population. For the last few months, I’ve been overcoming my fear. One of my approaches is volunteering to teach Tableau to the APAC analytics community at work. I’ve also watched many videos on public speaking and read a few books on presentations. I find these particularly helpful:
- ► Overcome Your Public Speaking Anxiety With These Tips by Eric Edmeades (31:03)
- ► How to Speak by Patrick Winston (1:02:43)
- ► The Presentation Secrets of Steve Jobs: How to Be Insanely Great in Front of Any Audience by Carmine Gallo
2. Problem-solving
Data analysis is about being presented with a problem and carrying out the necessary investigative tasks to find the answer. So, it’s evident that problem-solving is another essential skill for data analysts. A decent amount of analytics is about critical thinking and knowing the right questions to ask. Sometimes we may not know much about the subject and therefore not know what the right questions are, and that’s ok. I let my curiosity guide me in those circumstances and ask even seemingly dumb questions. Over the years, I’ve gotten better at not disallowing myself to ask questions for fear of coming across as stupid.
I described above more problem-solving skills applied to work when collaborating with teams. There is another aspect of its application. Mining and organizing data don’t happen with a simple click of a button, even though we have cool technologies to help us. Technologies don’t always run smoothly. It’s very common to encounter hiccups in our applied steps in ETL tools, lines of codes etc. we must be able to find and troubleshoot the problem.
3. Commitment to your craft
With the rapid rise of data, there has been an explosion of technology. We need to be in the know and keep up with the emerging trends in this field. We mustn’t fall behind. I think it can be costly in the long run if we don’t invest the time and discipline ourselves to learn continuously. I commit to learning something new every day. I recommend that you schedule 1 hour each day for learning, the ROI on this over time can be very profound. These are the sources I refer to:
- Books
- Online-contents like blogs, YouTubes
- MOOCs- Udemy and Datacamp are two I mainly frequent
- Conference- these are great for networking but can be pretty costly. One way to get around the cost is to ask work if they can cover the cost or volunteer as a helper.
There are many other soft skills that are relevant to succeeding as a Data Analyst. What are your top 3 essential soft skills for Data Analysts? Whatever they are, be sure to invest the time in developing and improving those skills. It’ll enable you to rise to new heights in your career.