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INFORMATION MANAGEMENT > INPUT DATA ANALYTICS > Causal Inference Engine

Data analytics technologies drive information management for critical decision-making for cyber security, risk, fraud, compliance, insider/outsider threats, production/services quality issues and public/environmental safety concerns. Currently there are two types of data analytics technologies.

  1. Causal Inference engine that perform input data analysis for qualitative analysis for answering the "why and how" question.

  2. Statistical Inference engine that perform output data for quantitative analysis for answering the "what" question.

Unless you use qualitative analysis, you can't explain things with quantitative data.

Causal inference engine matches input data patterns, validates single events and discovers enterprise logic and patterns. The causal inference engine evaluates the input data stream against the business process logic to assure the validity of the input data. If the input data is found to be anomalous, an alert is generated to stop the processing or implement other preventive actions. Input data can be analyzed at bus speeds with absolute accuracy because the process logic is known and the technology requires only a few cpu cycles to evaluate the input data.

Single Event validation is the holy grail of Information management and the value is illustrated in the diagram below.