Sarah Danzi

Alumni (MIDS 2020)


Data mining for anomalies in expected behaviors


In reviewing my academic and career choices, a central theme may not immediately emerge. I was a double major in Computer Science and Film with elective courses in seemingly every department. Likewise, expanding the review to my professional endeavors does not provide easy answers. My employment has centered on national defense, but the projects on which I’ve worked are as varied as my undergraduate studies. Examples include nation state cyber defense, sovereign border solutions, and space and reconnaissance systems. Each domain is unique in the details of its challenges. However, the unifying element of my background is at the heart of why I wish to study data science.

Fascination for me has never centered around one subject. It is the act of exploring a subject and making sense of it that I find most interesting. With this understanding, the disparate projects I’ve supported find common ground: the root of each effort’s success relied on the system’s ability to ingest and analyze the data available to it: that success depended on my ability to understand the problem space and identify, organize, and construct solutions using traditional data structures and algorithms.

Data science, though not new, has emerged as a prominent area of interest for future enhancement to these traditional approaches. It’s an area I first gained greater exposure to a year ago when asked to support a concept exploration initiative. It instantly peaked my curiosity on the technology and has motivated me to pursue an advanced degree in the subject. My purpose in attending UC-Berkeley's MIDS program is to gain the skills necessary to better exploit data to maximize its value and usefulness in making mission decisions.

Last updated:

June 5, 2023