Cambridge Semantics Named SIIA Business Technology CODiE Award…
At Cambridge Semantics, we have always focused on giving enterprises the ability to fully integrate text data with structured data, providing businesses with a more holistic view to make decisions with confidence.
Boston, Massachusetts (PRWEB)
June 16, 2017
Cambridge Semantics, the leading provider of Big Data management and analytics solutions, today announced that its Anzo Smart Data Lake® (Anzo SDL) solution was named a finalist in the ‘Best Text Analytics and Semantic Technology Solution’ category for the 2017 Software & Information Industry Association (SIIA) CODiE Awards.
Finalists represent the best products, technologies, and services in software, information and business technology. The winning solution will provide the most comprehensive set of tools and services to analyze structured and unstructured content whether privately held or publicly available.
For over 30 years, the SIIA CODiE Awards have been the premier awards recognizing product excellence within the software and information industries. This year’s awards offer 93 categories organized by industry focus of education technology and business technology. Anzo Smart Data Lake was honored as one of 206 finalists across 58 business technology categories.
“I am impressed by the level of innovation and creativity of the products that have been selected as this year’s CODiE Award finalists,” said Ken Wasch, President of SIIA. “We are happy to recognize these products and the power they have to transform the future of how we do business.”
Cambridge Semantics’ Anzo SDL platform uses semantic graph models to link and contextualize diverse enterprise data at scale. The graph models in Anzo SDL provide users with self-service data discovery, analytics and visualization capability across all entities and relationships in the data lake. Anzo SDL includes the in-memory graph database, Anzo Graph Query Engine, which recently shattered a previous record of loading and querying a ‘trillion triples’ by 100x.
“At Cambridge Semantics, we have always focused on giving enterprises the ability to fully integrate text data with structured data, providing businesses with a more holistic view to make decisions with confidence,” said Alok Prasad, president of Cambridge Semantics. “We are seeing ever-growing demand for this kind of capability. That’s why we are so pleased to be recognized by the prestigious CODiE Awards as a finalist in the Best Text Analytics and Semantic Technology Solution category. It is a testament to our leadership in this space.”
The SIIA CODiE Awards are the industry’s only peer-recognized awards program. Business technology leaders including senior executives, analysts, media, consultants and investors evaluate assigned products during the first-round review which determines the finalists. SIIA members then vote on the finalist products and the scores from both rounds are tabulated to select the winners. Winners will be announced during the CODiE Award Business Technology Winner Announcement & Celebration, July 25 in San Francisco.
Details about each finalist are listed at http://www.siia.net/codie/Finalists
About the SIIA CODiE™ Awards
The SIIA CODiE Awards is the only peer-reviewed program to showcase business and education technology’s finest products and services. Since 1986, thousands of products, services and solutions have been recognized for achieving excellence. For more information, visit http://www.siia.net/CODiE.
About Cambridge Semantics
Cambridge Semantics (CSI), the Smart Data Company, is an enterprise smart data management and exploratory analytics company. It enables customers and partners to rapidly build and deploy Smart Data Lake solutions based on its award-winning Anzo Smart Data Platform™ (Anzo SDP).
IT departments and business users gain better understanding and data value through the semantic linking, analysis and management of diverse data whether internal or external, structured or unstructured. The Anzo Smart Data Lake solutions are delivered with increased speed, at big data scale and at a fraction of the implementation costs of using traditional approaches.
The company is based in Boston, Massachusetts.
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