DIC 2014 - International symposium on Data Intensive Computing

Data analytics is critical to businesses. As the small data transforms into ‘Big’ data, traditional mechanisms and IT infrastructure used to support, analyze and make meaningful interpretations become ill suited. This also brings up numerous management issues. For example, IT experts have the responsibility to map organization-wide data by breaking down organizational silos and building an enterprise-wide IT infrastructure for data analytics purposes. This in fact requires next-generation analytical tools and techniques and brings up new challenges related to issues such as smart data distribution, quick response in the event of grid failure, etc. Whether one wants to arrive at some marketing decisions or fine-tune new product launch strategy, data analytics approaches can be a key to several business and societal problems. Also the threats being faced by the corporate due to privacy, frequent transfer of data over LAN and internet (specially Cloud) addressed. Applications and experiments in all areas of science are becoming increasingly complex and more demanding in terms of their computational and data requirements. Some applications generate data volumes reaching hundreds of terabytes and even petabytes. Analyzing, visualizing, and disseminating these large data sets has become a major challenge and data intensive computing is now considered as the ''fourth paradigm'' in scientific discovery after theoretical, experimental, and computational science.