Search Solutions

Data lakes are raw data ecosystems, where large amounts of diverse data are retained and coexist. They facilitate self-service analytics for flexible, fast, ad hoc decision making.

The I-BiDaaS project aims to empower end-users to utilize and interact with big data technologies more easily.

Our technology allows organizing the data according to their multidimensional attributes while building stratified samples at high-speed.

SOFIA DSS is a model and data-driven system that addresses the challenge of personnel evaluation and recruitment.

OptiqueVQS is a visual query formulation tool for expressing information needs in terms of queries over ontologies. OptiqueVQS is composed of an interface and a navigation graph extracted from the underlying ontologies.

BigDataStack will deliver a complete high-performance data-centric stack of technologies as a unique combined and cross-optimized offering that addresses the emerging needs of data operations and applications.

The key concept proposed in the DEEP Hybrid DataCloud project is the need to support intensive computing techniques that require specialized HPC hardware, like GPUs or low-latency interconnects, to explore very large datasets.

Key motivation of Cross-CPP project is to give cross-sectorial industries access to the great spectrum of sensor data coming from products from various industrial sectors (vehicles, smart home devices, etc.).

The EW-Shopp toolkit aims at helping companies operating in eCommerce, Retail and Marketing industries improve their efficiency and competitiveness by supporting weather and event-based integration and analytics of data collected by companies during the shopper’s journe

ABSTAT is an ontology-driven linked data profiling framework that aims to help users in an effortless understanding of the data.