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Graph data visualisation for cyber-security threats analysis

 In this blog post, we will offer an overview on how to deal with Security information and event management/log management (SIEM/LM) data overflow. Let’s see how Linkurious’ advanced graph visualisation solution helps easily identify and investigate cyber-security threats. Switching to a data lake architecture is often a required first step for analysts who wish to use graph […]

Linkurious brings DataStax Enterprise Graph technology “to life”

Linkurious now fully supports DataStax Enterprise Graph. We’re very excited to partner with DataStax to help their clients find value in their data and enable them to use it for fraud detection, cyber security and intelligence analysis. DataStax Enterprise is a graph database solution based on the open source Apache Cassandra architecture. Datastax provides support […]

Linkurious sponsors Connected Data London 2016

Linkurious is proud to sponsor Data to Value‘s Connected Data 2016, taking place on July 12th in London. Join us to discover the range of connected data problems that practitioners are tackling around the world. Connected Data London 2016 is the only event that brings together the Semantic Web, Linked Data and Graph Data disciplines under one roof. Web, […]

Investigating Enron’s email corpus: The trail of Tim Belden

In fraud and white collar crimes, forensic investigators often have to go through massive amounts of complex connected data to gather proofs and evidence for their cases. In the recent years, the development of graph databases and data visualization tools have made it much easier to quickly find information that would have taken days to […]

Linkurious sponsors GraphConnect Europe 2016

Linkurious is glad to sponsor Neo Technology’s GraphConnect Europe 2016, taking place on April 26th in London. Join us to discover how graph database technologies are changing the world and how Linkurious can help you understand the connections in your data. You’ll be able to see Linkurious in action and particularly how it can be […]

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