Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of ...

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 ...

The graph database market, driven by AI, is growing at a rate of almost 25% annually. Graph databases support knowledge graphs, providing visual guidance for AI development. There are multiple ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it makes ...

A new generation of graph databases has taken hold, and a generation of query languages has arrived alongside them. The assorted graph database query languages include the likes of Gremlin, Cypher, ...

Understanding the relationships in graph database theory allows us to work with the new 'shape' of data itself. Businesspeople like graphs. C-suite executives are fond of pie charts, Venn diagrams, ...

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, ...

Douglas Adams once wrote of a Holistic Detective Agency. The central character in this story, Dirk Gently, was able to solve cases with his understanding of the fundamental interconnectedness of ...