“Rapid application development” (RAD) refers to an approach to designing and developing computer applications. In public health and healthcare, we are not taught about application development – but it’s good for us to learn about it, since we have to deal with data from health applications. My blog post talks about the RAD approach I […]
Category Archives: Data Science
Posts about data science topics.
Understanding legacy data is necessary if you want to analyze datasets that are extracted from old systems. This knowledge is still relevant, as we still use these old systems today, as I discuss in my blog post.
Front-end decisions are made when applications are designed. They are even made when you design a survey in SurveyMonkey. What health data analysts often don’t realize is that these decisions have a profound impact on the quality and accuracy of the data that are collected through these front-ends, which is the focus of this blog […]
Reducing query cost is especially important in SAS – but do you know how to do it, or what it even means? Read my blog post to learn why this is important in health data analytics.
Curated datasets are useful to know about if you want to do a data science portfolio project on your own. I made this blog post for our group mentoring program. Check out the ones I am promoting on my blog!
Statistics trivia for data scientists will refresh your memory from the courses you’ve taken – or maybe teach you something new! Visit my blog to find out!
Management tips for data scientists can be used by anyone – at work and in your personal life! Get the details in my blog post.
REDCap mess happens often in research shops, and it’s an analysis showstopper! Read my blog post to learn my secret tricks for breaking through the barriers and getting on with data analytics!
GitHub beginners – even in data science – often feel intimidated when starting their GitHub accounts and trying to interact with the web page. Don’t be shy! Catch the highlights from a recent GitHub beginners workshop I held!
ETL pipeline documentation is great for team communication as well as data stewardship! Read my blog post to learn my tips and tricks.