“Everyone in this country should learn to program a computer, because it teaches you to think.” — Steve Jobs
Today, I want to talk about coding versus problem solving as it relates to data science and data analytics. So, this past weekend I hosted a Data Analytics workshop. I sat with a couple of aspiring data scientists and data analysts to walk through my process. What we do in the workshop is provide case studies and we walk through the process of loading information from a spreadsheet or database, extracting data and create a visualization for business purposes. One of the questions that kept coming up was, “Hey man, what about machine learning? What about AI and things like these high level things?” Because that’s what most people hear when they hear data science. But, my response was, “The reality of the situation is, data science is more about problem solving than actual coding.” Data Analytics is a profession and it all starts with the data and the problem.
The best way involves a) having a framework and b) practicing it.
“Almost all employers prioritize problem-solving skills first.
Problem-solving skills are almost unanimously the most important qualification that employers look for….more than programming languages proficiency, debugging, and system design.
So, let’s for instance say, we have a video product. I’m trying to help a client to grow their video product because they release videos on a regular basis, and their goal is to get more views, likes, more email subscriptions to grow revenue and to make more money, right? So how would we think about this? So, we should look at the places where videos are being released, in this case Facebook, Instagram, Youtube, and a website. We would look at the analytics which is the information that is provided from these places. Google Analytics, Instagram, YouTube all provide this information for you about how well you’re doing or not. So, I would take all this information, put it together maybe in a spreadsheet, perform some analysis and think about different questions and answers as it relates to grow their videos to create more of the results they want. Thinking through the problem is not really coding, right? You have to know how to code to extract and model data but also being able to think through a problem is just as important and adds as much value as actual coding.
I’ve met people who writes very eloquent code, but if you’re coding and it doesn’t solve a problem, what’s the point? Overall that’s what I wanted to talk about in this post, and say that, thinking through problems, doing projects, walking through case studies, and using your tools which is coding, process mapping, visualizations is very important. That would be my advice to any aspiring data scientists out here. I’m having an intro to data analytics class next month. Leave your thoughts or comments below.
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Intro to Data Analytics
