Cambridge Semantics is updating its Anzo data discovery and integration platform with features that enhance the treatment of unstructured data, according to a press release. The company is referring to its new capabilities as “unstructured data 2.0”, and Anzo’s workflow has been rearchitected from an embedded to distributed architecture. The update provides better workflow and work process management, as well as the ability to scale Anzo for large data integrations at faster speeds.
Trademarked ‘The Smart Data Company’, Cambridge Semantics is a data management and analytics provider that offers a semantic layer to connect enterprise data. The company’s flagship product, the Anzo Smart Data Lake, allows users to link, analyze, and manage enterprise data in a variety of formats including structured, unstructured, internal, and external.
Cambridge Semantics Anzo also features a redesigned user interface, optimized to simplify the process of onboarding unstructured data. This, according to the vendor, will make it easier for customers to work with the platform. Additional updates to Anzo include improved automation in onboarding workflows, query builder enhancements, new administrative tools, and a beta version of Kubernetes-based GraphMart’s cloud deployment.
In a press statement, the company’s co-founder and CTO Sean Martin spoke about the release, adding: “Anzo has always differentiated itself in the market by allowing customers to treat unstructured data as a first-class citizen and this latest version of Anzo raises the bar even further. We are committed to helping guide the industry with the best tools available to help organizations transform their data management and analytics operations.”
Solutions Review named Cambridge Semantics one of 4 Machine Learning Data Catalog Vendors to Watch in 2019 earlier this year.
Latest posts by Timothy King (see all)
- The Best Data Management Events and Conferences to Attend in 2020 - January 14, 2020
- Solutions Review Releases 2020 Buyer’s Guide for Data Management Software - January 14, 2020
- 7 Data Management Compliance Predictions from 5 Experts for 2020 - January 10, 2020