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Data Automation & Reporting Tool

Overview

Developed a Python tool that extracts data from a database and processes three CSV files. The system cross-checks records against multiple controls and generates a comprehensive multi-sheet Excel report, including summaries, detailed records, and control-specific data. Key Results: Reduced manual processing time from hours to minutes Eliminated human errors and ensured data consistency Delivered structured, ready-to-use reports for business use.

πŸ—„οΈ
SQL
πŸ“„
CSV
βœ”οΈ
Check
πŸ“Š
Excel
πŸ“€
Output
πŸ—„οΈEstrazione DB| Connessione e query SQL
20% pipeline completata
πŸ“Š 4 fogli Excel
βœ”οΈ 5 controlli superati
❌ 2 errori evitati
LOG IN TEMPO REALE
  • 422ms SQL β†’ 3.200 righe estratte
  • 1842ms 3 file CSV caricati
  • 292ms Controlli: 5 superati, 2 KO
  • 182ms Excel generato: 4 fogli
  • 562ms Report inviato via email
⏱️ TEMPO RISPARMIATO
Manuale2hvs4mAutomatico
per 5 report generati
πŸ—„οΈ Estrazione dati Β  πŸ“„ CSV Β  βœ”οΈ Controlli Β  πŸ“Š Report Β  πŸ“€ Output
πŸ† RISULTATI PRINCIPALI
Riduzione tempi da ore a minuti
Eliminazione errori umani
Report strutturati e pronti all’uso

Details

This tool automates data extraction from a database and processes three CSV files. It cross-checks records against multiple controls and generates a comprehensive multi-sheet Excel report, reducing hours of manual work and ensuring data accuracy. Features: Automated Data Extraction: Connects to a database and extracts data using a custom Python script. CSV Cross-Validation: Loads and cross-checks data from three CSV sources. Multi-Sheet Excel Report: Generates an Excel file with: Summary Sheet: Count of records passing each control. Details Sheet: All records with corresponding control results. Additional Sheets: Control-specific detailed information. Error Handling & Logging: Robust error handling and logging to ensure traceability. Analytics: Provides summary and detailed analytics for quick business insights. Key Results: Reduced manual processing time from hours to minutes. Eliminated human errors and ensured data consistency. Delivered structured, ready-to-use reports for business needs. How It Works: Data Extraction: Extracts data from the database via a custom Python script. Data Processing: Loads and validates data from the extracted source and the three CSV files, applying multiple controls. Report Generation: Produces a multi-sheet Excel report with summary, details, and control-specific sheets. Output: Delivers ready-to-use Excel reports for business decision-making, automatically sent by email to the target recipient. Tech Stack Python: Core scripting and automation Pandas: Data processing and manipulation CSV & Excel: Data input/output SQL: Database extraction