This vanity site is my outlet for infrequent posts on building communities of practice in data analytics. I am an R enthusiast and follow a wonderfully supportive open source community all over the world. This content does not represent the views of my employer in any way.
MS Business Analytics, 2020
University of Notre Dame Mendoza College of Business
University of Wisconsin Parkside
BS Mechanical Engineering
Iowa State University
My short list of useful books, courses, and expert blogs. Many are free. These could be departure points for your own learning journey. My hope is that you take and copy sections for sharing with your own community of practice. Yes, I am giving away all of the secrets. One of the things that I spend a lot of time thinking about is how to communicate about data science with other human beings.
Mapbox web services APIs for #rspatial data science projects
The composition of American generations per Pew Research & the US Census
Cycling 🚲 popularity has grown in 2021 as evidenced by local cycling club activity and US national surveys. Some of this may be related to changes like new e-bike configurations and city-wide bike share systems that make it accessible to more people. It’s also possible that post-COVID, many people still want fun & affordable exercise. Bike shops have been busy filling orders and making repairs. Lead times for some models are months long as global supply chains work to catch up.
More often than not, the most impactful analytics projects do not involve any artificial intelligence. The real financial return comes from insights delivered to the organization via Exploratory Data Analysis, or EDA. Analytics professionals who focus on decision science, that is, people that use data to provide ground truth to the business, must be able to articulate what the EDA process is and what the standards are for the process. Analysts should be the best people available to find meaning in the data.