The data science and non data science podcasts that you should be listening to. Podcasts are my #1 source of entertainment, outside of my children, and education, outside of day to day learnings at my job. I’ve picked up my playlist over the last 10 years or so (has it really been that long)? Here’s my list of favorite podcasts. Many of these are a top of a lot of Data Science podcasts lists, others you’ve probably never heard of.
I cohosted an interview with the host of the Towards Data Science podcast “Climbing the Data Science Ladder”, Jeremie Harris! Jeremie also is a co-founder of a Data Science mentorship program called SharpestMinds.
Have you ever heard a marketer complain about sales wasting their hard earned leads? Have you ever witnessed a support department blame Friday deployments on high time to resolution numbers? Have you ever wondered why your longer tasks’ cycle time seems to balloon? Well wonder no more!
Open offices represent a large portion of all office space. Chances are, if you are reading this at work, you work in an open office environment. The tech community seems to be a particularly vocal proponent of this environment. We often cite the increase in collaboration as being the reason why an open office is preferred.
It can be challenging taking large complex datasets, boiling them down to their essentials, and explaining the results to the rest of the company. It becomes infinitely more difficult when your analysis is questioned because the data you used appears to contain a paradox that those with tertiary knowledge do not understand. This is a guide to how to handle one of the most common paradoxes in analytics.
Focus on the wrong metrics and your company is doomed. Vanity metrics do not contribute to your ability to create, refine, and make future decisions. These metrics are distractions. Vanity metrics are dangerous.
There’s a lot of goal setting frameworks out there. Between ORKs, SMART Goals, BHAGs, or even Goal Pyramids (like Rockefeller’s Strategic Planning Pyramid) you’ll choose some specific goals that are measurable, actionable, audacious (but achievable), and time limited. I’m not going to tell you how to set goals or even that you should set goals (there may be harmful effects). I will, however, tell you that unless you are willing to analyze the results don’t even waste your time setting goals.