For a few hours on a Sunday I try to read something from the list of books, articles, emails, and other things ignored during the work week. There seemed to be more than usual this week so here are a few insights from the pile.
One of the best things about a blog is the archive.
Second only to the relationships I have grown with so many of you.
First, here is a podcast episode I keep listening to and sharing.
Important distinctions should be made between skills and knowledge. I absorbed this through the lens of my work life but I think this is broadly applicable anywhere.
Sprinkle it everywhere.
I am listening to a podcast episode of Minds Behind Maps. This one is particularly timely. Bruno Sanchez is the, Program Director of the Planetary Computer at Microsoft and the author of "Impact Science: The science of getting to radical social and environmental breakthroughs".
Knowledge can be placed in buckets, skills should not--Bruno Sanches
Anyone working in a scientific field recognizes these buckets. They are deep and not connected willingly from within. We spend so much time positioning our expertise and “othering" our colleagues into their buckets--perhaps to simplify dragging them from the stage of debate.
Bruno brilliantly explains what we lose when we don’t value skills but instead strain our necks to see if the knowledge checklist has been evaluated. My point remains that your scientific, technical, mathematical, focus ignores that we often need more than the facts.
“How many people need to die before we understand that facts are not enough? One? Ten? A thousand? This is a blunt question to draw attention to the failure in facts alone, even when lives are at stake.”--Bruno Sanchez, Impact Science, The Science of getting to radical social and environmental breakthroughs.”*affiliate link
Many either new to or trying to elevate careers in data science aren’t feeling the love.
We read the debates over which degree, school, or path to a career in data is the best.
Hiring managers want the work done. They value critical thinking skills and how you solve problems. The ability to ask data questions and revise them when needed is critical. I would call it common sense but you might already know--it isn’t as common as you think.
Do the work, get the skill--the subject knowledge will grow with you.