Predictive Monitoring for Power BI

Predictive monitoring for Power BI uses usage, performance, capacity, and design signals to identify risks before they affect users. Instead of reacting to slow reports, refresh failures, throttling, or rising Fabric costs, teams can prioritize the reports, semantic models, workspaces, and users that need attention first.

Wiiisdom helps teams detect high-footprint reports, inefficient semantic models, costly queries, noisy neighbors, and peak usage patterns that can silently drain capacity. By turning these signals into prioritized recommendations and approved remediation actions, organizations can reduce waste, avoid preventable throttling, and plan capacity with more confidence. Microsoft solutions such as Fabric Unified Admin Monitoring, or FUAM, help centralize Fabric and Power BI tenant telemetry, activities, inventory, and capacity usage. Wiiisdom complements this native monitoring layer by turning those signals into predictive, data-driven governance: intelligent scoring, business-ready prioritization, early risk detection, lifecycle controls, certification workflows, and agentic remediation. Instead of waiting for an incident to be visible and reacting after the fact, Wiiisdom helps teams anticipate what may go wrong, understand what matters most, and take controlled action before users, compliance, or costs are impacted.