As you view the metro-like map of the skills needed for data science, you will quickly notice that this relatively new discipline utilizes just about every tool within an ORSAs toolkit. The goal of the data scientist is the same as any other analyst; helping leaders make better decisions. The challenge, however, of getting the critical pieces of information to support the decision is entirely different.
To get an idea of the type of challenge facing a data scientist, let’s think a little bit about the kinds of problems they are working on for the military. ORSAs within cyber organizations have to deal with cyber-related alerts to the Army network. Imagine all the antivirus, phishing attacks, and other warnings that occur from the millions of laptops, desktops, mobile devices across the Army’s network. Without going into the details, just extracting a small sample of that information is not a trivial task, and then to organize the data into a meaningful way to do analysis is another challenge onto itself. These types of tasks focus on approaches to munge or transform data from its raw unstructured form into something structured for analysis.
Another challenge facing data scientists involves using various methods of artificial intelligence, such as machine learning, to train computers to do tasks that can augment humans. For example, image classification is one of the first applications of machine learning. You can imagine how we could leverage the same types of algorithms to assist imagery analysts in identifying an enemy and friendly systems.
These two small examples are just a tiny fraction of the myriad of applications for data science. Just like the other techniques of operations research, data scientists will help solve issues spanning across every aspect of the Army enterprise.