SinoXiv
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results found
Dynamic data distributions, system failures, and low-latency, cost-effective processing are becoming more of a challenge to modern real-time data pipelines. Current streaming architectures are based o...
Self-healing data pipelines
Reinforcement learning
Stream processing
Cost-aware optimization
Real-time validation
Adaptive systems
Anomaly detection
The current data validation systems are mostly reactive, static, and resource-heavy which may lead to interruptions of pipelines and will not be able to detect data corruption in real-time settings. T...
Predictive Data Validation
Self-Healing Data Pipelines
Reinforcement Learning
Graph-Based Validation
Data Quality Assurance
Autonomous Data Systems
Spatio-Temporal Graphs
Intelligent Data Engineering
