Paco Nathan

Paco Nathan
Evil Mad Scientist,

Website | @pacoid

Data Scientist for Concurrent in SF, and a committer on the Cascading open source project. 10+ years leading innovative Data teams, 25+ yrs in tech industry overall. Background in math/stats and distributed computing. Expertise in Hadoop, R, AWS, predictive analytics, machine learning, NLP


Hadoop in Practice Great America Ballroom K
Paco Nathan (
Average rating: *****
(5.00, 2 ratings)
This talk examines the notion of a "workflow" as a general abstraction for common use cases encountered in Data Science, particularly for building Enterprise apps. Patterns of workflows provide recipes for integrating different frameworks, plus the means for optimizing large-scale apps. We review this approach in the context of a sample app based on the Cascading open source project. Read more.


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