We present Stratosphere, an open-source software stack for parallel data analysis.
Stratosphere brings together a unique set of features that allow the expressive, easy, and …

Big Data analytics has recently gained increasing popularity as a tool to process large
amounts of data on-demand. Spark and Flink are two Apache-hosted data analytics …

Data clustering is one of the fundamental techniques in scientific analysis and data mining,
which describes a dataset according to similarities among its objects. Partition based …

With problem size and complexity increasing, several parallel and distributed programming
models and frameworks have been developed to efficiently handle such problems. This …

Abstract Big Data Analytics has the goal to analyze massive datasets, which increasingly
occur in web-scale business intelligence problems. The common strategy to handle these …

Many big data applications such as smart transportation, healthcare, and e-commerce need
to store and query large collections of small XML documents, which has become a …

The ability to process large numbers of continuous data streams in a near-real-time fashion
has become a crucial prerequisite for many scientific and industrial use cases in recent …

Governments are increasingly publishing their data to enable organizations and citizens to
browse and analyze the data. However, the heterogeneity of this Open Government Data …

We present AMADA, a platform for storing Web data (in particular, XML documents and RDF
graphs) based on the Amazon Web Services (AWS) cloud infrastructure. AMADA operates in …

The amount of data in the world is expanding rapidly. Every day, huge amounts of data are
created by scientific experiments, companies, and end users' activities. These large data …