This blog post was co-authored by Styliani Pantela, Matthew Saltz, and Eden Zik.
We started off on Saturday by giving a workshop on Vertica Analytics, where we covered architecture, use cases, and our machine-learning options. The students asked great questions and were excited about getting the chance to begin their own projects.
Over the course of 24 rigorous hours, the 17 teams (each composed of 3-5 students) worked on projects related to social good–partnering with organizations such as Uplift (Communities Against Sexual Violence), Partners in Health, and Wellesley’s own Office of Disability Services.
The three of us helped mentor teams, and seeing the resulting final projects was both exciting and rewarding.
Besides looking out for great intern candidates–of which there were many–we challenged teams to use Vertica in their hacks by giving them a running cluster on AWS and a starter kit. We offered prizes for the best use of Vertica (HP tablets and Raspberry PIs), and over a third of the teams decided to take us up on our offer!
We judged 6 great Vertica hacks, including the following:
- A tool that uses text messaging to request medical supplies from Partners in Health in areas with poor Internet access (first place).
- A site to help college students coordinate sharing of expensive textbooks (runner-up).
- An aid for people with disabilities to find wheelchair accessible routes.
Despite the fact that many of the people using Vertica had never used a database before, they were able to learn SQL and get their apps working overnight (#awesomedocs).
Hackathons are a great place to find motivated employment candidates and to spread the word about Vertica to people who might one day decide to build something big on our platform! Not to mention the rewarding experience of mentoring students who are just getting started.
Eden, Stella, and Matthew
Stella works as a systems engineer for the Query Engine team where she optimizes query execution.
Matthew is a software engineer on the Analytics team where he’s working to expand the machine learning platform and to add new machine learning algorithms.