Short Description: Applying generic aggregation or analytical algorithms to raw data, combining these results with domain-specific business knowledge, to produce strategic, actionable insights or alerts.
Full Description: This WorkFlow involves a process of analysing data and parameters to produce meaningful information or inferences (models), which help in decision-making (for humans). Decision support can be purely analytical or cognitive (eg deep learning). Examples of decision support include crop pest alert systems, clinical decision support systems, etc. Common decision support WorkFlow involves capturing raw data using collection tools; filtering the data through the application of algorithms to extract parametric values; and interfacing with analytics and business intelligence tools for combinatorial and statistical analysis of parameters. This allows specific indicators of symptoms, behaviour, and outcomes of the system to be obtained, and to interface with knowledge management tools to interpret the situation, and predict possible causes, future outcomes and suggestions for corrective actions if any. It can also learn and improve the accuracy of interpretation, prediction and correction using feedback collected from users, and by tracking system responses to corrective actions.
Other Names: Analytics
Sample mappings of workflows to use case:
- Agriculture: Market linkage: Support decision making on harvest timing and best seed selection based on local conditions
- Education: Remote learning: Data-driven analysis of teacher and student performance for informed school development
- Health: Maternal and newborn health: Analyze test results to determine treatment/therapy planning