For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of ...

Context, not content, now drives AI visibility, making structured data the strategic data layer every enterprise must ...

In the new knowledge-based digital world, encoding and making use of business and operational knowledge is the key to making progress and staying competitive. Here's a shortlist of technologies ...

When enhanced by the rich, self-describing nature of semantic knowledge graphs, data mesh and data fabric can greatly complement one another.

Knowledge graphs—machine-readable data representations that mimic human knowledge—are bridging the gap between proprietary enterprise data and safe, reliable, helpful LLMs.

Think of knowledge-graph-powered data catalogs as the search engine for the data in the enterprise.

Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

Available starting today, Neo4j Aura Graph Analytics is said to work with any kind of data source, including Oracle, Microsoft SQL, Databricks, Google BigQuery, Snowflake and Microsoft OneLake.

K is for Knowledge: Application and data integration for better business, using metadata and knowledge graphs Being disrupted by Big Tech is one of the greatest concerns for any business.

The "Graph Item Type" does not default to "AREA", so be sure to select that for a traditional graph that looks like a rolling hill of data. It's safe to leave "Consolidation Function" to AVERAGE, and ...