SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
Distributing the Sloan Digital Sky Survey Using UDT and Sector
E-SCIENCE '06 Proceedings of the Second IEEE International Conference on e-Science and Grid Computing
UDT: UDP-based data transfer for high-speed wide area networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Bigtable: a distributed storage system for structured data
OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
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We define analytic infrastructure to be the services, applications, utilities and systems that are used for either preparing data for modeling, estimating models, validating models, scoring data, or related activities. For example, analytic infrastructure includes databases and data warehouses, statistical and data mining systems, scoring engines, grids and clouds. Note that, with this definition, analytic infrastructure does not need to be used exclusively for modeling but simply useful as part of the modeling process. In this article, we discuss the importance of analytic infrastructure and some of the standards that can be used to support analytic infrastructure. We also discuss some specialized analytic infrastructure applications and services, including applications that can manage very large datasets and build models over them and cloud based analytic services.