Data Governance & Analytics
First make data clear (ontology), then make data speak (analysis & prediction)
Powered by the knowledge engine's ontology and the recommendation engine's algorithms: ontology → governance → analysis → prediction turns multi-system data into trustworthy decisions.
Core Capabilities
01
Ontology modeling
Establish shared semantics for equipment, materials, customers and processes — what they are, their attributes and relationships. The conceptual bedrock shared by data governance and the knowledge graph.
02
Data governance
Data standards, master data management, data quality and lineage — making multi-system data trustworthy and usable.
03
Big data analytics
Metric systems and operations dashboards, conversational querying, anomaly and opportunity insight.
04
Prediction & recommendation
Staged recommendation (cold start → growth → mature) and Bayesian-family prediction: e-commerce selection & conversion, manufacturing quality & capacity, mining equipment failure & safety alerts.
Four steps
First make data clear, then make it speak — ontology is the bedrock shared by data governance and the knowledge graph.