Custom Full-Code Automations
Some of the Projects I've done for my clients.
Data privacy note:
All project visuals are presented with anonymized and AI-generated sample data. Original client information (including names, numbers, and identifiers) has been removed. No confidential or personally identifiable client data is displayed.
FP&A Revenue Report Generator
Finance teams were struggling to consolidate revenue data spread across thousands of .csv and .xlsx files from various global regions, currencies, and clients. The manual process was time-consuming, error-prone, and inconsistent. I built a standalone desktop application in Python that automates the full data pipeline—from ingesting raw transactional files to generating a clean, formatted Excel-based revenue report segmented by country, market section, client, and currency. The GUI-driven tool includes built-in logic for currency normalization, time-based filtering, data validation, Excel pivot table creation, and automatically sending the report through email.
Key Value I Delivered
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Developed a Python desktop app with GUI for file/folder selection, filtering, and reporting—no code or Power BI required by end users.
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Automated the ETL pipeline to load millions of rows from nested .csv/.xlsx files, standardize column formats, extract transaction dates from file paths, and unify the structure.
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Built currency normalization logic, merging real-time exchange rate files to calculate USD equivalents and flag missing or invalid rates.
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Generated multi-sheet Excel reports with built-in pivot tables: Revenue by Country, Revenue by Market Section, Totals per Client, and Time Series by Month (charts and slicers were added with VBA automation).
Key Value I Delivered
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Enabled date filtering, allowing users to slice datasets by custom time periods before generating reports.
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Designed auto-formatting and styling logic in Excel: merged headers, stylized tables, adjusted column widths, and removed gridlines for presentation-ready deliverables.
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Integrated search functionality with Selenium to look up client names directly from the app via Google.
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Added a "Send via Email" feature that prepares a mailto draft with the report, streamlining communication with stakeholders.
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Implemented error handling + logging throughout the codebase for full traceability and debugging.
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Used modular design with clean helper functions and logging to ensure scalability and maintainability.
