fp-and-a

OM Core - open-source multidimensional modeling engine.

Financial Analyst & FP&A portfolio | Excel financial modeling, budgeting, forecasting, variance & profitability analysis, Power BI, SQL, Python & executive reporting.

Read-only MCP server for FP&A & management reporting — governed metrics, financial statements and drill-down over a SQL semantic layer. Your own financials on your own warehouse, not market data. Open core of Précis. (metric engine · ClickHouse · OIDC · Docker)

经营管理导向财务分析看板：用 Python 将财务报表与业务明细转化为可离线运行的 FP&A 管理驾驶舱，含风险检测、杜邦分析、营运资本、利润中心与投资敏感性分析。

Excel dashboard to identify overspending across departments and highlight areas requiring immediate cost control

A practical, non-coding Excel / Power BI-ready FP&A project for a B2B SaaS company. The model forecasts monthly cash inflows, outflows and balances; compares Budget vs Actual; analyzes AR, AP and working capital; tests Best/Base/Worst scenarios; predicts cash shortages; calculates runway; and presents management recommendations through an executive

Free Claude Code skill + the certified-BI doctrine from kymira.ai: business intelligence where every number reconciles to the file's own totals.

Decision-focused FP&A, finance BI, Power BI, and valuation case studies with downloadable models and audit controls.

FP&A Analysis Toolkit

End-to-end financial analytics architecture integrating IFRS financial modeling, a PostgreSQL-based financial data warehouse, Python forecasting models, and Power BI executive dashboards.

AI skills for CFO & Finance teams — connects GitHub Copilot and M365 Copilot to Dynamics 365 Business Performance Analytics via live DAX queries.

Four-page Power BI financial performance dashboard built from the SQL case-study dataset with 21 DAX measures, executive KPIs, and budget tracking.

Agentic FP&A & ERP Analytics Copilot using Python, SQL, ML, forecasting and data visualization.

End-to-end FP&A and BI case study: Financial Reporting, Budget vs Actual, Power BI, DAX, Power Query and CAPEX Analysis.

End-to-End Retail Analytics Project using Walmart sales data. Built a master dataset, performed monthly sales analysis, budget vs actual reporting, variance analysis, store and department performance evaluation, and sales forecasting using Holt-Winters Exponential Smoothing.

Budget vs actuals → driver-attribution variance commentary, not just numbers. Agentic AI for FP&A.

Plataforma de inteligência econômica que transforma indicadores oficiais em recomendações para revisão das premissas do Forecast.

FP&A-style budget vs actuals variance analysis using Python, SQL and Power BI, with management commentary and business recommendations.

Single-file interview tool for the AI-capability module of an FP&A hiring loop

Driver-based rolling revenue forecast on dbt and DuckDB with base, upside, and downside scenarios and a leak-free backtest that measures accuracy honestly: 3.61 percent MAPE, a 42 percent improvement over a seasonal-naive baseline, guarded by dbt tests.