As enterprises continue to navigate the complexities of digital transformation, connected data is becoming an increasingly common necessity. Connected data is when data assets are linked together to ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the generation of plausible-sounding but factually incorrect information. KAIST ...

A graph database can help you discover connections in your data you never imagined; here’s how to get started Alaa Mahmoud is an advisory software engineer and master inventor at IBM Analytics Cloud ...

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 ...

When Emil Eifrem, founder and CEO of Neo4j, was working for an enterprise content management startup in Sweden in the mid-2000s, he was struggling with the challenge of mapping relationships between ...

The problem: The app must store a collection of people and who they know. Sometimes it must find out everyone who knows someone who knows Bob. Sometimes it must look further for everyone who is three ...

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 ...

Graph databases, such as Neo4j, Apache Spark GraphX, DataStax Enterprise Graph, IBM Graph, JanusGraph, TigerGraph, AnzoGraph, the graph portion of Azure Cosmos DB, and the subject of this review, ...

The relational database is primarily oriented toward the modeling of objects (entities) and relationships. Generally, the relational model works best when there are a relatively small and static ...