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Cambridge Semantics Introduces Geospatial Analytics within its Award-Winning AnzoGraph® DB
  • USA - English

AnzoGraph® DB Now Combines Scalable Location Analytics with Relationships and Graph Analytics


News provided by

Cambridge Semantics

Jun 18, 2020, 08:00 ET

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BOSTON, June 18, 2020 /PRNewswire-PRWeb/ -- AnzoGraph® DB Now Combines Scalable Location Analytics with Relationships and Graph Analytics

Cambridge Semantics, the leading provider of graph-driven data integration and analytics software, today announces the addition of geospatial analytics within its award-winning AnzoGraph® DB. This new capability combines the power of scalable location analytics with the power of relationships and analytics in a graph database.

Many knowledge graph projects today include the need to know about people, things, and events in the real world and where they happened. Adding geospatial capabilities to AnzoGraph DB enables users to determine a location and its relationship to borders, regions, zones, or other places – and then help users perform calculations and queries about those locations and their relationships.

The use cases for geospatial analytics are varied and extensive. In the public sector, communities can use it for managing emergency services, mapping, city planning and predicting crime. In financial services, geospatial is key for assessing risks and determining risk zones. Geospatial is often a key enabler for many other business processes, including IoT projects, tax fee assessment, setting up delivery and sales zones, and optimizing routes. In addition, geospatial analytics can aid a variety of COVID-19 applications, including contact tracing.

"Geo-spatial data is a vastly underused asset in most organizations. One of the primary reasons for this under-use is because spatial data often needs to be connected and related to other data. And capturing those relationships outside of a graph database is difficult. This is why Cambridge Semantics' geospatial announcement is to be welcomed," said Philip Howard, Research Director at Bloor Research.

Unlike relational databases, the underlying data model of graph databases is based on nodes, their properties, and connecting edges that express relationships to much more effectively represent the world around us. By including geospatial coordinates and their relationships in a graph, the resulting data models are far more versatile for processing semantics, geometry, topology, as well as harmonizing that information with multiple other sources of unstructured and structured data for analytics.

"The integration of geospatial analytics within AnzoGraph DB is another example of how Cambridge Semantics continues to push the boundaries of knowledge graph innovation and to show what is possible with graph-based analytics," said Steve Sarsfield, Vice President of Product, Cambridge Semantics. "Further, the extensive applications for geospatial analytics will help our partners and corporate innovation teams leverage geospatial for their large-scale, location-based intelligence applications."

Key functions of AnzoGraph DB with geospatial analytics include:

  • As a customizable database, AnzoGraph DB uses its own user-defined function capability, or GeoSPARQL to provide over 160 functions to perform geospatial analysis.
  • Define Regions – Define polygon points and circles on your map. The regions can be two dimensional or three dimensional.
  • Use common shape data files – Define zones with common geospatial files. Use these predefined maps to understand counties, tax zones, flood zones, precincts, and much more. Formats supported: SHP, GeoJSON, KML, WKT, and WKB.
  • Understand relationships – Use the geospatial functions to understand if two zones overlap, touch, or are unconnected. Understand whether a point of interest is in a zone or not.
  • Convert coordinates – It is often necessary to convert between two or more coordinate systems when working on problems in 3D space. AnzoGraph DB includes the algorithms to convert between Cartesian, Spherical, Cylindrical, and Elliptical coordinate systems.
  • AnzoGraph DB conforms to Open Geospatial Consortium (OGC) standards.

AnzoGraph® DB is the only MPP (massively parallel processing) graph database designed to accelerate data integration and scalable analytics. It offers graph analytics at performance levels that compare favorably with the industry-leading data warehouse analytics products. It includes regular line-of-business analytics along with views and windowed aggregates, as well as inferencing, graph and data science algorithms to support in-graph feature engineering and transformations. Application developers can extend AnzoGraph by building their own custom functions and aggregates that can perform in parallel across enterprise-scale knowledge-graphs. Further, AnzoGraph® DB is the only standards-based graph database supporting both open W3C SPARQL 1.1/RDF standards and an upcoming version of Cypher on the same data.

About Cambridge Semantics
Cambridge Semantics Inc., The Smart Data Company®, is a modern graph-driven data integration and enterprise analytics software company that enables seamless access, integration and analysis of all enterprise data via a graph-driven data fabric architecture.

Cambridge Semantics award-winning Anzo® is a modern, graph-driven data integration platform that connects and brings meaning to information from any system across the enterprise. The company's AnzoGraph® DB product is based on open standards and is the fastest & most scalable graph database supporting data integration and rich analysis with graph algorithms, data warehouse-style analytics, plus feature engineering for Machine Learning and more.

The company delivers products and solutions that enable IT departments and business users across Life Sciences, Financial Services, Government, Manufacturing, and other industries to accelerate data delivery and to provide meaningful insights across the organization at hyper-speed and scale.

Visit http://www.cambridgesemantics.com or follow us on Facebook, LinkedIn and Twitter: @CamSemantics.

SOURCE Cambridge Semantics

Related Links

http://www.cambridgesemantics.com

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