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.

As data complexity continues to grow and the demand for real-time insights increases, the move away from traditional relational databases and towards the adoption of graph databases will become vital.

When given access to multiple enterprise data stores, graph databases can offer entirely new insights and capabilities. Yu Xu is CEO of TigerGraph.

Data Interpretation is an important part of the Quantitative Aptitude section in many competitive exams. It tests the ability ...

The Graph, the decentralized indexing system that works much like Google for blockchains, has introduced a data standard for Web3. Called GRC-20, the standard would define how information is ...

The data referenced in the graph is not based on direct temperature measurements either, he said. Instead, temperatures are inferred based on the types of oxygen locked in the ice core samples.