Connected data has become a central element of
analytics projects and solutions.
A knowledge graph is a natural data model with the capability to harmonize and integrate data as well as apply algorithms and analytic functions needed for connected data analytics.
As an enterprise-scale knowledge graph platform, Anzo allows users to rapidly build scalable knowledge graphs to connect data from multiple sources – iteratively remodeling the data as required for new analytics use cases. Anzo’s in-memory graph engine, AnzoGraph, provides entire libraries of graph algorithms, data science functions and traditional OLAP analytics functions that can be combined in the same query to tackle any analytics problem, at scale, within the knowledge graph. Anzo’s query generation capability allows non-technical users to express complex analytic questions without writing queries or code.
APPLY WAREHOUSE ANALYTICS AND GRAPH ALGORITHMS TOGETHER, AT SCALE
Apply advanced analytics to highly blended datasets in a knowledge graph to find previously hidden insights. Built-in libraries of hundreds of data science primitives and analytic functions/formulas support traditional OLAP and graph specific analytic functions as well as data science, ML/AI, and geospatial functions.
DEEP INTEGRATION WITH DATA SCIENCE PLATFORMS
Leverage and exploit investments in data science platforms and algorithms by applying them to highly optimized blended datasets in a knowledge graph. Built-in deep integration with data science platforms through the Apache Arrow Flight Protocol, HTTP/REST APIs, and user-defined-extensions (UDX).
