دانلود کتاب داده های بهداشتی عملی – رام کردن پیچیدگی داده های دنیای واقعی

A few years ago, I was at the Google Faculty Institute, where I met Noah Gift during one of the lunch breaks. We got to talking about academia and education, and many of the challenges and opportunities we saw when it came to empowering people to become experts in data. Whether this was data engineering, data science, or even the more basic aspects of programming, we both saw the potential for fundamentally changing how knowledge is disseminated. It was shortly after this conversation that Noah floated the idea of writing a book. While I had considered this previously, it was a fleeting thought and not something I had seriously considered. I filed the conversation away in the back of my mind and figured it could be the focus of my sabbatical (I was still in academia at the time). A year later, everything was flipped upside down by COVID-19 and the world’s response. Despite having just received tenure and promotion, I decided to leave academia and return to industry—rolling up my sleeves and getting back into the thick of it. I was a few months into my first project (building a clinicogenomic database that pulled data from a handful of hospitals) when I started to see opportunities to help educate our teams on how we could improve our approach to dealing with the complexities of electronic health record (EHR) data. By then, we were deep into the pandemic and all riding the roller-coaster of repeated loosening and tightening of the many COVID restrictions. Every day, I saw news articles and reports that were making a desperate attempt to draw conclusions from all of the data and anecdotes about the number of infections, mortality rates, false positives/ negatives, and so forth. As someone who had been working with healthcare data for years, I found it very challenging to listen to data scientists, epidemiologists, public health professionals, and even lay people draw conclusions and make serious decisions based on what I knew was very dirty and faulty data.