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After two Gartner Data & Analytics (D&A) Summits in 2023 it’s clearer than ever that knowledge graphs and generative AI will play central roles in modern data and analytics, increasing time-to-value across industries and use cases.
Stardog was predicated on a long-term bet that data management and knowledge management were on a collision course, set out by Google, and that Knowledge Graph was the intersection point. From 2023’s perspective, it looks like our long-term bet was correct.
It was wonderful to see our customers, long-time friends and new faces alike this week in NYC at the Knowledge Graph Conference (KGC).
This blog post will show you how easy it is to get started with knowledge graphs using Stardog Cloud.
As you might have heard, Stardog is applying Large Language Models (LLMs) to enterprise knowledge graph technology. So what does this actually mean?
In this article, you’ll understand the three types of Knowledge Kits offered by Stardog, their use cases, and how to access them. Spoiler alert: they are all free.
We’re at the beginning of a revolution in machine-understandable semantics powered by Large Language Model breakthroughs. Stardog Voicebox, powered by LLMs, will fundamentally flatten the enterprise knowledge graph (EKG) implementation cost curve.
Stardog 9 includes a range of new features and enhancements that enable organizations to more easily connect their data, people, and processes, while also improving performance, scalability, and security.
Stardog is now SOC 2 Type II certified.
Stardog’s VP of Product Navin Sharma provides his perspectives and key takeaways from the recent Gartner Data & Analytics summit.
The “metrics layer” is the oldest and foundational semantic layer use case. But there’s a new breed of semantic layer use cases that Stardog and its customers are pioneering.
The challenges and opportunities of five common areas of data friction: Data culture, data model, data integration, data interrogation, and data intelligence.