One technology experiencing a kind of renaissance is the graph database, which has existed for years but is finding new relevance in current cybersecurity contexts. (NicoElNino/Getty Images) Spurred ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

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It's often easier to understand the use cases for graph databases than understanding how graph databases work. For instance, asking the question of who the most powerful thought leaders across ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Master Data Management is a practice adopted when a company really gets serious about making use of its data. Based on recent trends and some emerging analyst research, it seems that when companies ...

Graph databases are gaining attention as enterprises work on their next-generation artificial intelligence (AI) applications. While still a bit of an outlier, graph-oriented databases continue to find ...

IBM today announced the general availability of Graph, a service for the Bluemix cloud offering that the company said helps set up a relatively new, high-performing type of database. Graph databases ...

This post is one of a series that introduces the fundamentals of NOSQL databases, and their role in Big Data Analytics. What is a graph database? Graph databases organize facts into connected bundles, ...

Graph databases, which explicitly express the connections between nodes, are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. That ...