Adam Breindel has over 15 years of successes working with cutting-edge technology for small startups, as well as major players in the travel, media/entertainment, and financial industries. He has been teaching front- and back-end technology for more than 8 years. In addition to web sites, GUI applications, and mobile device software, Adam has built streaming analytics for one of the world’s largest banks, and produced a modern integration to a 1960s-vintage mainframe app for one of the world’s largest airlines. His big data work has also included fraud modeling and scoring for debit card transactions. Adam focuses on designing and coding systems in a way that yields predictable results, leverages best practices and high-productivity tools, minimizes excess code, and is fun to do.
Democratizing has become a bit of a buzzword, and why not? Institutions of all types and sizes are discovering that almost every role touches a bit of large-scale data analysis or data science, and sometimes more than just a bit! In this talk we'll look at the patterns, strengths, and weaknesses of three different open-source tools, which all claim to make large-scale computation simpler, easier, and more accessible to more people. Our exploration will reveal not only major differences at the technical level, but also differences in culture, documentation, usability, open-source governance, and other areas. How easy are they to use, for real people in real organizations?
We'll look at: