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.

🗄️

SQL

📄

CSV

✔️

Check

📊

Excel

📤

Output

🗄️Estrazione DB| Connessione e query SQL

20% pipeline completata

📊 4 fogli Excel

✔️ 5 controlli superati

❌ 2 errori evitati

422ms SQL → 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

🗄️ Estrazione dati 📄 CSV ✔️ Controlli 📊 Report 📤 Output

🏆 RISULTATI PRINCIPALI

Riduzione tempi da ore a minuti

Eliminazione errori umani

Report strutturati e pronti all’uso

Details

The problem

Business data is scattered across multiple systems — databases, spreadsheets, ERP APIs — each with a different format. Consolidating this data manually into coherent reports takes hours, introduces transcription errors and produces results that are already out of date by the time they are read.

The solution

A Python automation system that connects to all configured data sources, extracts and normalises the data with pandas, runs quality checks and generates complete Excel or PDF reports ready for distribution. The entire pipeline runs on a schedule — daily, weekly or on demand — without any manual intervention.

How it works

1. Connection to database via SQL queries 2. Download and normalisation of CSV and ERP API data with pandas 3. Automated quality checks: missing values, duplicates, anomalies 4. Calculation of KPIs: totals, averages, trends, comparisons 5. Generation of formatted Excel report with charts 6. PDF export and automatic send via email 7. Historical archive of reports for monthly trend analysis

Typical results

Reduction of manual reporting time from 30–60 minutes per day to zero. Immediate access to up-to-date KPIs every morning. Complete elimination of copy-paste errors between systems. Consistent, professional reports ready for management review.