Welcome back to the Meet Our Team Q&A series. My name is Daniela Williams, Project Manager at ISE, and I’ll be asking ISE team members questions to help give insight into what makes us tick.
Today I'm interviewing Tawni Burger, Software Engineer, and one of our resident Big Data gurus.
Q. How long have you worked at ISE and what did you do prior?
Tawni: I have worked at ISE for just under a year and a half. Prior to ISE, I was working at DST Systems, headquartered in Kansas City, as my first developer position after graduation. I had worked there for two years primarily developing web services in Java that interacted with a mainframe for financial transactions.
Q. What got you interested in Data Analytics?
Tawni: I was originally majoring in Biochemistry and Molecular Biology for my undergrad degree. However, I quickly found out that doing lab work for hours at a time was not interesting to me, only the analysis of the results. From there, I became interested in bioinformatics, which is essentially data analytics for biological systems. I switched majors to Computer Science and continued to read articles relating to bioinformatics. When I decided to start a Master’s degree, I contemplated getting a degree in bioinformatics, but chose to go the more generic data analytics route that would be applicable to any domain.
Q. Data Analytics is more than just analyzing data. What are the stages in the life cycle of a data analysis project?
Tawni: There is a standard practice in the data science community for the lifecycle of a data analysis project called CRISP-DM (cross-industry process for data mining). It provides a framework for data scientists to plan and execute a project. There are six major phases to the methodology, shown below. These six phases are Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The process is an iterative one, meaning going back and forth between different phases is expected.
Data Analysis Project Lifecycle (photo source)
Q: This year you attended the ACM SIGKDD Conference on Knowledge Discovery and Data Mining. What new knowledge from the conference were you able to apply to your projects at ISE?
Tawni: First off, the conference was an astounding wealth of knowledge! There was so much to learn in all aspects of data mining. In my key takeaways blog post I mentioned a couple of techniques I learned about at the conference; time series analysis with matrix profiles and survival analysis. I have not had the appropriate project to apply survival analysis to yet, but I have indirectly applied some of the time series analysis techniques to my current project. In addition to these techniques, I feel strongly that attending the conference has opened my mind to new ways to look at a problem, and thus creating unique and well-fitting solutions.
Q: What do you do for fun?
Tawni: In my downtime I enjoy spending time with my husband and our three dogs (all Beagles). I also enjoy tasting craft beers and indoor gardening.We grow lettuces, jalapenos, bell peppers, tomatoes, cucumbers, and a variety of herbs indoors. The philosophy behind it is that it is cheaper, fresher, and more easily available than store-bought produce. I also play the occasional video game and work on personal projects from time to time.