Hazy: Making It Easier to Build and Maintain Big-Data Analytics. - KUMAR, ARUN; NIU, FENG; RÉ, CHRISTOPHER (Communications of the ACM, 2013)
The article discusses the construction and maintenance of Big-Data analytics systems as of March 2013, focusing on machine-learning methods and statistical methods while describing the Hazy project for algorithm management. Topics include trained systems, interfaces between algorithms and systems, the GeoDeepDive application for the statistical analysis of geological research papers, and the Bismarck project for infrastructure abstractions. Data sets, probabilistic logic programming, debugging, convex programming, and scalability are mentioned.