Workshop on Distributed Data Analysis with Applications in Finance and Healthcare: March 21-22, 2016

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The application deadline is February 1, 2016.

Description:

One of the primary aspect of Big Data is about leveraging all the data sources available within an organization which often comprise of structured data, semi-structured and unstructured data, and publicly available data on the internet. The transformative power of Big Data analytics is to combine all of these data sources into a single collaborative data model, rapidly iterate on the data, apply analytics, and generate insights from the combined data analysis. Big Data are often distributed on the cloud or at the edges of the Internet of Things (IoT), which brings challenges and new opportunities to the design and development of the underlying mathematical or statistical models. The technology infrastructure, such as distributed data storage, computing and modeling platform, streaming of data source into a model and outcomes from a model to the edge device, must be sufficiently developed to keep pace with the need for business insights and ensure scalability and flexibility as data grows.

The research focus of this workshop is on the explorations of the methodology for the computing and modeling architecture for distributed data, including data ingestion and staging platform, enterprise data warehouse and analytics platform. The application focus of this workshop is on two major areas: Healthcare and Finance. The workshop will bring academic researchers and industrial engineers together for the exploration and scientific discussions on recent cutting-edge theories and proven best practices in industries on distributed data analytics.

Directorate liaison: Sujit Ghosh

Workshop Organizers:
Bo Zhang
Xiangxiang Meng, SAS Institute
Wayne Thompson, SAS Institute

Please send questions to [email protected]