Don't let big data upend your business knowledge or your operational expertise. Use it to augment them.
By fusing human and organizational expertise with the analytical power of big data, the precision of scientific modeling and the rigor of multi-context reasoning, Albeado’s PRISM based solutions reveal significant new insights that would otherwise be inaccessible to either human or machine alone.
PRISM exposes and illuminates previously unseen patterns, linkages and associations among and between disparate events. Powerful new perspectives are gleaned. Assumptions are validated. Causal inferences are preplayed. Forecasts are tested. Predictions are made with high confidence. Decision-making gets transformed.
Precision Pharma Marketing: Predicting Network Influence of Key Opinion Leaders
Optimizing Pharma Operation: Accelerating Clinical Trials
Agile Pharma R&D: Predicting and Interpreting Drug Interactions
Predicting personalized risk of hospitalization and readmission
Alerting Fraud, Abuse and Wastage – in Real Time
Optimizing Patient Flow and Resources in Hospital ED
Enhance cyber-security, improve reliability, increase safety
Identify precursors of system outages
Analyze causation of anomalies
Boost key customer service metrics
Solidify regulatory compliance
Make asset health and work flow management reliable, cost effective
Ensure payment channel integrity
Uncover cross-domain nexus
Rapidly adapt to changing Regulatory Demands
Personalize products and services
Explosion of operational data needs a transformative contextual analysis to result in actionable insights. Streaming data has immense richness that can be extremely valuable if one could analyze it in a timely fashion. Learning from data alone however is inadequate. Learning needs augmentation from human expertise and support of scientific modeling to become prescriptive. Without combined power of multi-context reasoning, expert systems and knowledge modeling, most data only analytics lack the high confidence causal inference that decision making depends on.
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