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.
ποΈ
SQL
π
CSV
βοΈ
Check
π
Excel
π€
Output
ποΈEstrazione DB| Connessione e query SQL
20% pipeline completata
π 4 fogli Excel
βοΈ 5 controlli superati
β 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
β±οΈ TEMPO RISPARMIATO
Manuale2hvs4mAutomatico
per 5 report generati
ποΈ Estrazione dati Β π CSV Β βοΈ Controlli Β π Report Β π€ Output
π RISULTATI PRINCIPALI
Riduzione tempi da ore a minuti
Eliminazione errori umani
Report strutturati e pronti allβuso
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