AnzoGraph: a W3C Standards-Based Graph Database
Jo Stichbury interviewed Barry Zane, our VP of Engineering and creator of AnzoGraph™, for Towards Data Science to find out more about how graph analysis and W3C standards are coming together and his predictions on the future of graph databases.
Ontology and Data Science
In this KDnuggets article, Favio Vázquez explains how ontologies are the stepping stones to creating a Data Fabric by establishing relationships between your data points that not only represent sharable and reusable knowledge, but also adds new knowledge about them.
2019 Trends in Machine Learning: Unclogging the Bottleneck
In this article for AI Business, Jelani Harper discusses with our own CTO, Sean Martin, and other thought-leaders the bottlenecks preventing more rapid adoption of Machine Learning and how graph technology can help eliminate some of them.
DBTA Trend-Setting Product in Data and Information Management for 2019
Each year, Database Trends and Applications magazine looks for product offerings that promise to help organizations derive greater benefit from their data, make decisions faster, and work smarter and more securely. Cambridge Semantics is proud to have been spotlighted in this year’s list of Trend-Setting Products for 2019.
Impeccable Machine Learning Productivity: The Wonders of Data Provenance for Predicti …
In this article for AI Business Sean Martin, our CTO, discusses how the superior chain of provenance created by graph databases allow organizations to operationalize machine learning models with data as similar as possible to that used in training.
3 Use Cases for Unstructured Data
TDWI research reveals that organizations that utilize disparate data for analytics are more likely to measure a top- or bottom-line impact from their analytics efforts than those that do not. In this article for TDWI, Fern Halper discusses three potential use cases for unstructured data.