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.
KMWorld Trend-Setting Products of 2018
KMWorld magazine has named Cambridge Semantics’ Anzo Smart Data Lake solution a ‘Trend-Setting Product” for 2018. This award is reserved for products that embody innovation, imagination and evolution and reflect the ingenuity of their developers and the diversity of invention.
Is The Enterprise Knowledge Graph Finally Going To Make All Data Usable?
In this article for Forbes, Dan Woods points to Siri, Alexa and Google Home as everyday examples of the power of knowledge graphs and how AnzoGraph can similarly make all enterprise data usable with an Enterprise Knowledge Graph.
The Enterprise Knowledge Graph Phenomenon: What it Means to Artificial Intelligence
This article in AnalyticsWeek discusses the presence and overall worth of enterprise knowledge graphs, particularly for AI applications, with insights from a number of industry thought leaders including Cambridge Semantics’ VP of Marketing John Rueter, CTO Sean Martin and VP of Engineering Barry Zane.
Is GOLAP the Next Wave for Big Data Warehousing?
In this article for Datanami, Alex Woodie interviewed our CTO, Sean Martin, and our Vice President of Engineering, Barry Zane, about the difference between OLTP and OLAP graph databases and why graph OLAP databases are the future of big data warehousing.
Are Semantic Connectors The Key To Scalable Graph ETL?
In this article for Forbes, Dan Woods introduces the concept of ‘semantic connectors’, which he believes will help immensely in making graph ETL work better and how Cambridge Semantics’ process is made a lot easier by employing semantic standards like RDF and OWL.