Show me the ontology: any data catalog powered by a knowledge graph should have a visually documented ontology, a formal representation of the entities in the graph and explanations as to how they’re ...

In a modern data catalog, data and analysis flow into a knowledge graph that traces the connections and relationships across your data, teams, and processes. The knowledge graph keeps data ...

Sometimes, you can enter into a technology too early. The groundwork for semantics was laid down in the late 1990s and early 2000s, with Tim Berners-Lee's stellar Semantic Web article, debuting in ...

Concomitant to the rise of data products, 2023 will see the introduction of the “data products catalog,” which will further extend the reach of current data catalogs in use across a number of ...

The semantic technologies underpinning RDF knowledge graphs are primed for data mesh and data fabric architectures — and their synthesis. They’re certainly ideal for crafting data products.

“If you just give it, ‘Here are 180 million column names, figure it out,’ it’s going to be overwhelmed in the same way you and I would be overwhelmed. By building a semantic layer – this thing that is ...

Generative AI depends on data to build responses to user queries. Training large language models (LLMs) uses huge volumes of data—for example, OpenAI’s GPT-3 used the CommonCrawl data set ...

TL;DR Key Takeaways : GraphRAG uses knowledge graphs instead of traditional vector databases, allowing deeper insights and relationships within datasets through structured data representation.

Knowledge Graphs, by contrast, represent data as a network of nodes (entities) and edges (relationships). They can handle more complex, nuanced queries based on the types of connections, the ...

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 ...