KNOWLEDGE-DRIVEN FEDERATED BIG DATA QUERY AND ANALYTICS PLATFORM

• Main Authors: Cuddihy, Paul, Kumar, Vijay Shiv, Aggour, Kareem Sherif, Weisenberg Williams, Jenny Marie, Vinciquerra, Anthony Joseph
• Format: Patent
• Language: English
• Published: 10.09.2020
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS

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. 0 a)L. I .1 n gD ,L IIl 01 CN CuD 0 a)I 0I x CDiCi C.) ( C C cc 0u It C)CJ cu CD C CD 0) 0 ~ ('o co CL() C I 1 1 1 I ) 0 cc I0 CU CUx~ C,, ?) U) EI -T 2" L D c) CD0 2>1 00 0 Cc A- -§'Cu) UO 0 ' (.) U) >: Cu-4 C; 00I (L) (L - IM ccIc c Li:Cq --I ;--- --- --- 0i CI C( ) Cuf uo!1se~u 818a