Speaker
Jim Pivarski
(Princeton University)
Description
Even though both involve programming, data analysis is a different activity from software engineering, with different best practices.
However, the recent interest in functional programming as a good practice for parallelization applies to data analysis as well. We'll mix theory (immutable data, structural sharing, combinators) with practical examples in Spark and (possibly) other functional programming-based analysis frameworks.
Minimal prerequisites in specific language and framework knowledge (we'll introduce what we need), but a flexible mindset helps.