It feels like I can’t go a week of datascrolling without hearing someone pose the distinction between learning technical skills and business skills as a data analyst.
I get the question, I really do. I was an econ major, so I understand scarcity — there’s only so much time to learn, so what provides the better value? Many will claim that the business skills go overlooked and that aspiring analysts focus too much on being geeky.
Of course it’s true that a successful analyst places every effort to driving the business goals, not just the models. At the same time, data has become so intertwined with today’s economic and business landscape that it can be impossible to separate these skillsets.
How to bridge the gap between technical and business skills is something I was hoping to write about for some time, and I’m grateful to offer a guest post to the Pragmatic Institute on the topic. Pragmatic is a well-known skills accelerator with origins in product marketing and recent moves into data science and analytics.
You’re welcome to share your thoughts in this post’s comments. If I can help your or your team operate on the “two lungs” of analytics (read the post for an explanation), don’t hesitate to get in touch.