DanaC 2015 - 4th workshop on Data Analytics at Scale

Ata nowadays comes from various sources including log files, transactional applications, the Web, social media and many others. A large part of this data is generated and transmitted in real time and in a large scale. To create value out of these data sets, business analysts and scientists employ advanced data analytics techniques combining, among others, traditional BI, text analytics, machine learning, data mining, and natural language processing. Tackling the complexity of both the data itself and its analysis remains an open challenge.
Cloud computing has emerged as a cost-effective and elastic computing paradigm that facilitates large scale data storage and analysis. Cloud infrastructures can provide adaptive resource provisioning with very little initial investment while scaling to massive amounts of commodity computing nodes. Data analytics, being very resource intensive, 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, systems and data analytics techniques in the new cloud computing environments remains an open challenge.