Abstract: A system for querying a federated data store includes a metadata knowledge graph describing the contents and relationships among one or more underlying data stores, an interactive user interface receiving requests from a data consumer, a predefined constrainable query (‘nodegroup’) store containing predefined constrainable queries that define data subsets of interest across one or more of the underlying data repositories, a knowledge-driven querying layer generating and executing queries against the federated data store and merging responsive results, a scalable analytic execution layer receiving the search results from the federated data store and applying machine learning/artificial intelligence techniques to analyze the results, and a user interface presenting visualizations of raw or analyzed results to the consumer. A method and a non-transitory computer-readable medium are also disclosed.

Abstract: A system to query a federated store containing disparate data types and stores, the system including a UI or API to specify query details, a metadata knowledge graph with metadata describing the contents of the data stores, the relationships among them, and how to programmatically query the data stores, a predefined constrainable query (‘nodegroup’) store containing nodegroups providing a template to search the data stores, the querying layer including services and libraries to process nodegroups and generate a set of queries, a query and analysis platform providing the set of queries to at least one data store for execution at the federated stores and return a result, a scalable analytic execution layer applying machine learning/artificial intelligence techniques to analyze the query results and presenting data analysis result visualizations. A method and a non-transitory medium are also disclosed.