학술논문

More than the Sum of its Parts : Building Domino Data Lab
Document Type
Conference
Source
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. :9-9
Subject
data science
data science organization.
data science scalability
domino data lab
industrial machine learning
Language
English
Abstract
Industry has always leveraged cutting edge quantitative research techniques. From finance and insurance, to marketing and manufacturing, efficiencies and advantages have been seized through measurement, prediction, and the generation of insights' but never at this scale. Organizations which previously may have employed one or two data scientists are now scaling the work to dozens if not hundreds of practitioners. Where previously only a handful of organizations could boast that they were leveraging machine learning and statistical models, now it's a rarity to find an untouched industry or player. Organizations are now faced with the challenges of empowering, scaling, and measuring this workforce to sustain the transformation to the prediction economy. In this talk, I will discuss how and why we built the Domino Data Lab platform. I will talk about the challenges we faced technologically, organizationally and culturally when bringing a system of record to data science.

Online Access