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fpanda

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Retail-Value-Driver-Management-Plateform

Enterprise-inspired Analytics Engineering platform demonstrating how operational retail data can be transformed into executive decision support using Python, SQL Server, and Power BI.

  • Updated Jul 1, 2026
  • Python

GL journal screener that reads every entry instead of sampling: 1M journals through 7 explainable audit rules (Benford, splits, round numbers, off-hours) in 13s, flagging 95.7% of seeded anomalies and only 0.4% of clean entries. Measured, reproducible benchmarks included.

  • Updated Jul 27, 2026
  • Python

Month-end close task engine: models the close as a dependency DAG from YAML templates, logs work in an append-only audit event log, and runs a from-scratch Critical Path Method to name the tasks that actually stretch your close. 10,000-task analysis in 4s (measured); 39-task banking close template included.

  • Updated Jul 28, 2026
  • Python

Constant-currency consolidation engine that splits multi-entity growth into scope, organic, and FX translation impact. The bridge ties to reported figures with no plug line (max residual 1e-06 measured at 1,000 entities), exports an executive Excel workbook and Power BI-ready extracts.

  • Updated Jul 28, 2026
  • Python

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