Big Data Management Using Ontologies for CPQ Solutions

A Reference Architecture for Big Data Solutions

With big data technology and predictive analytics techniques, organizations can now register, combine, process and analyze data to answer questions that were unsolvable a few years ago. This paper introduces a solution reference that gives guidance to organizations that want to innovate using big data technology and predictive analytics techniques for improving their performance. The reference ...

High performance solutions for big-data GWAS

In order to associate complex traits with genetic polymorphisms, genome-wide association studies process huge datasets involving tens of thousands of individuals genotyped for millions of polymorphisms. When handling these datasets, which exceed the main memory of contemporary computers, one faces two distinct challenges: 1) Millions of polymorphisms and thousands of phenotypes come at the cost...

Real-Time Data Management for Big Data

Users have come to expect reactivity from mobile and web applications, i.e. they assume that changes made by other users become visible immediately. However, developers are challenged with building reactive applications on top of traditional pulloriented databases, because they are ill-equipped to push new information to the client. Systems for data stream management and processing, on the othe...

Web Data Management Ontologies

From Relational Database Management to Big Data: Solutions for Data Migration Testing

Enter Hadoop, the de facto open source standard that is increasingly being used by many companies in large data migration projects. Hadoop is an open-source framework that allows for the distributed processing of large data sets. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. As data from different sources flows into Hadoop,...