Unified Knowledge Graph Across Heterogeneous Systems
Transformed fragmented enterprise content into a unified, navigable knowledge graph, enabling cross-domain analysis and contextual understanding.
Situation
The client’s operational knowledge was distributed across multiple platforms and formats. There was no unified model to represent relationships between these data types, limiting the ability to perform holistic analysis or trace dependencies.
Solution
A data integration and modeling layer was implemented to normalize and interconnect disparate data sources. This graph served as the foundational layer for higher-level applications, including immersive visualization.
OUTCOMES
Challenges
Silos
- •Structured system silos
- •Documentation silos
- •Unstructured asset silos
Modeling
- •No unified schema
- •Missing cross-system relationships
- •Inconsistent entity definitions
Analysis
- •Limited holistic analysis
- •Weak dependency tracing
Solutions
API Data Ingestion
Aggregated data via APIs across multiple systems.
- Connected multiple enterprise systems through API integrations
- Collected data consistently across varied platforms
- Established a reliable ingestion layer for downstream modeling
Relationship Graph Model
Constructed a graph-based representation of entities and relationships.
- Represented entities and dependencies as graph structures
- Captured cross-system relationships in a consistent model
- Enabled flexible traversal across connected enterprise artifacts
Unified Content Schema
Mapped all content types into a unified schema.
- Standardized entity mapping across disparate systems
- Created a durable model for long-term extensibility
Downstream Relationship Layer
Exposed relationships for downstream visualization and interaction layers.
- Made relationship data available to visualization tools
- Supported immersive and analytical interaction layers
- Enabled higher-level applications to build on a common foundation
Source Integrity Preservation
Maintained references to original systems to preserve source-of-truth integrity.
- Preserved authoritative ownership in original systems
- Linked graph entities back to source records