Knowledge-driven federated big data query and analytics platform

A system to generate and run federated queries against a plurality of data stores storing disparate data types, the system including a user interface receiving query details from a data consumer, a metadata knowledge graph containing metadata for links and relationships of the data stores, a knowled...

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Bibliographische Detailangaben
Hauptverfasser: AGGOUR KAREEM SHERIF, CUDDIHY PAUL, KUMAR VIJAY SHIV, VINCIQUERRA ANTHONY JOSEPH, WEISENBERG WILLIAMS JENNY MARIE
Format: Patent
Sprache:chi ; eng
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Beschreibung
Zusammenfassung:A system to generate and run federated queries against a plurality of data stores storing disparate data types, the system including a user interface receiving query details from a data consumer, a metadata knowledge graph containing metadata for links and relationships of the data stores, a knowledge-driven querying layer accessing the graph and selecting predefined constrainable queries from a nodegroup store and applying the metadata links/relationships to the predefined constrainable queries to assemble subqueries, a query and analysis platform providing the subqueries to some of the datastores for execution, a scalable analytic execution layer receiving and aggregating search results from the data stores into a merged search result and/or obtaining analytic results by applying machine learning and artificial intelligence techniques to the distributed data, the user interface presenting visualizations generated from the merged search results, and/or the analytic results. A systemand a non-transitory compu