Oracle International Corporation

Matthew Lawrence Lontchar

Douglas Ray Cosby

Rahul R Kamath

Anurag Garg

Charles Randall Wilson

Narayan Madhavan Nayar

James Charles McCausland

A data management system receives updates to records of a source dimension. Some records of the source dimension reference target dimensions. The data management system identifies template records from existing records in the source dimension for modeling changes to connections with the target dimensions based on the updated records in the source dimension. The template records are discovered using rules-driven processes, AI-driven processes, or a serial or parallel hybrid processes including rules and AI. These processes use ancestor information from the updated records to find best-matching template records. The rules-driven processes additionally rely on matching fields, and the AI-driven processes additionally rely on vector embeddings and optionally clustering. Updates are made to the target records in the target dimensions, including any roll-up structures indicated for data propagation, identified using the template records, and downstream applications using the target records may consume the updates.

Rules driven application synchronization by automatically detecting different template nodes for different synchronization targets

Disclosed is a method, system, and computer program product for implementing adaptive business workflows, where the context is coordinated with a hierarchy. The adaptive workflow may include conditional stages that are also coordinated with the hierarchy.

Method and system for implementing an adaptive data governance system

Various techniques are disclosed herein for storing and managing master data in hierarchical data systems. Several related concepts, embodiments, and examples are disclosed, including techniques for incremental rationalization in a hierarchical data model, techniques for implementing governance pools in a hierarchical data model, techniques for application materialization in a hierarchical data model, techniques for data intersection mastering in a hierarchical data model, techniques for change request visualization in a hierarchical data model, and techniques for hierarchy preparation in a hierarchical data model.

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Avon Lake, OH, United States of America

Matthew Lawrence Lontchar