Build trusted Power BI models
Start with one outcome: build a model from data sources, trust KPIs, change PBIP safely, release with confidence, operate Fabric, or govern decisions. The plugin routes to a focused workflow and keeps PBIX binaries untouched. More
Skills 16 in the ChatGPT listing
Autonomous Exception Management Use when turning autonomous Power BI planning deviations into managed exceptions, including revenue gaps, risky backlog, unrealistic targets, biased models, sparse segments, owner hints, status, escalation, and closure evidence. Autonomous Forecast Agents Use when coordinating multiple AI forecasting perspectives for Power BI sales forecasts, including backlog, seasonality, budget, sales skepticism, risk, consensus, dissent, and explainable forecast arbitration. Autonomous Planning Loop Use when building or running a closed-loop autonomous Power BI planning cycle that refreshes actuals, forecast, gap detection, scenarios, actions, tracking, learning, and the next plan without changing PBIX files directly. Causal Forecasting Use when adding causal and counterfactual thinking to Power BI sales forecasts, including working days, holidays, delivery constraints, price changes, product lifecycle, stockouts, campaigns, customer behavior, and best/base/worst case simulations. Constraint-Aware Planning Use when constraining Power BI revenue planning by delivery, capacity, stock, supply, margin, cash, payment terms, sales resources, or operational feasibility rather than forecasting unconstrained demand only. Powerbi desktop Use when building Power BI models, trusting KPIs, changing PBIP safely, releasing, operating Fabric, or governing decisions. Fabric Next-Generation USPs Use when a Power BI or Fabric team needs FinOps, Copilot answer regression, Direct Lake readiness, data-product SLOs, capacity change proof, or executive decision traces. Forecast Trust Market Use when designing or evaluating a Power BI forecast trust market, human override tracking, sales and finance confidence scoring, forecast accountability, and self-learning model-vs-human accuracy loops. Forecast War Room Use when building a Power BI forecast war room or control tower for executive revenue review, forecast risk triage, top deltas, action ownership, gap closure status, confidence monitoring, and daily forecast operating rhythm. Goal-Seeking Planning Use when calculating what must happen to reach Power BI revenue, budget, roll, margin, cash, or service targets, including reverse planning, target-gap decomposition, required backlog conversion, and required demand uplift. Powerbi model wizard Use when starting a new Power BI model from a business goal, source list, star schema, KPI plan, security plan, and report-page plan. Planning Memory Use when storing and reusing Power BI planning memory across cycles, including forecast versions, assumptions, actions, overrides, actuals, error causes, segment lessons, and durable learning signals for autonomous planning. Planning Readiness Score Use when scoring whether a Power BI model and forecast pipeline are ready for autonomous planning, including data quality, backlog snapshots, order-to-invoice matching, model accuracy, bias, granularity, constraints, overrides, and action tracking. Revenue Digital Twin Use when designing or running a Power BI revenue digital twin for sales forecasting, target-gap simulation, backlog-to-invoice scenarios, what-if revenue paths, budget attainment, and forecast-to-cash decision support from an open Power BI Desktop model or exported forecast CSVs. Revenue Rescue Mode Use when turning Power BI sales forecast gaps into operational rescue actions, including backlog acceleration, customer activation, product substitution, delivery escalation, gap closure ranking, and forecast-to-action recommendations. Self-Healing Forecast Governance Use when Power BI forecast governance should automatically demote biased models, choose safer baselines, trigger data-quality blockers, adjust trust status, and protect planning from low-quality autonomous recommendations. 
