DanaC 2013 - DanaC: Workshop on Data analytics in the Cloud

Data analytics has the potential to be a transformer of scientific research, and data-driven business decisions. By effectively analyzing huge volumes of data, scientific research can be transformed from hypothesis-driven to data-driven, where forming scientific hypotheses will be aided by discovering patterns in vast quantities of data. For most technology companies that operate on a Web scale, analyzing customer data can provide insights on customer behavior, and lead to answers for critical business decisions.
Cloud computing has emerged as a cost-effective and elastic computing paradigm. Cloud infrastructures scale to massive numbers of commodity computing nodes and provide adaptive provisioning without prohibitive initial investments. Data analytics has the potential to be a significant cloud application, and to constitute a large fraction of the workload of modern data centers. Designing the infrastructures and systems for data management in the new computing environments remains an open challenge.
↑ top
Topics of Interest
Areas of particular interest for the workshop include (but are not limited to):
Parallel execution and optimization
Scalable storage and indexing
Workload management
Infrastructures for cloud computing
Scalable machine learning
Frameworks for parallel computing
Industrial experiences and use cases
Benchmarking, tuning, and testing
Data science and analytics
Privacy and security in the cloud
Multi-tenancy
Economic models for data
Data management and analytics as a service