The field of graph analytics was virtually unknown outside of the academic realm just a few years ago, but all that has changed with the market’s insatiable hunger for all things big data. The top two ...

How would you feel if you saw demand for your favorite topic — which also happens to be your line of business — grow 1,000% in just two years’ time? Vindicated, overjoyed, and a bit overstretched in ...

Neo4j is both the original graph database and the continued leader in the graph database market. Designed to store entities and relationships, and optimized to perform graph operations such as ...

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 ...

The latest trends and issues around the use of open source software in the enterprise. As defined nicely here by Hitachi Vantara’s Bill Schmarzo, “Graph analytics leverage graph structures to ...

Graph databases highlight relationships among the data elements that are otherwise invisible in a tabular format. Furthermore, the analysis is transformed from a descriptive viewpoint — analytics that ...

Even though graph analytics has not disappeared, especially in the select areas where this is the only efficient way to handle large-scale pattern matching and analysis, the attention has been largely ...

Recently, I had an enlightening conversation with Gemini Data about their approach to creating what I’m calling “semantic connectors.” These connectors will help immensely in making graph ETL work ...