metrics-dashboard

KPI dashboards combine metric definitions with calculation methods, data-source mapping, and anomaly-detection thresholds to surface actionable insights. This Skill guides you through five phases—requirements, KPI design, data architecture, visualization, and implementation—ensuring complete data lineage, quality checks, and agent-dispatch with defined output schemas for executive, operational, departmental, and board scenarios.

Map data sources to KPI definitions with explicit calculation methodologies, then implement quality checks and validation rules across your data architecture. This Skill provides complete data lineage documentation and validation frameworks to ensure KPI accuracy before visualization and deployment.

Yes. This Skill includes anomaly-detection thresholds and alert workflows integrated into KPI dashboards. You define detection rules alongside KPI metrics, then dispatch analytics agents with a defined output schema to monitor and trigger actions when anomalies occur.

This Skill covers implementation guidance for executive, operational, departmental, and board dashboard scenarios. Each follows the same five-phase workflow but tailors KPI selection, visualization, and data architecture to stakeholder requirements and decision-making contexts.

Establish complete data lineage, source-to-metric mappings, and quality-check procedures before visualization. This Skill requires mandatory objectives definition, KPI methodology documentation, and data-source validation to ensure dashboards deliver reliable, auditable insights.

Yes. After defining KPIs and data architecture, this Skill dispatches metrics-analyst agents with a defined output schema to implement visuals and automate monitoring workflows tailored to your dashboard type and stakeholder needs.