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Data Automation & Reporting Tool

pythonAutomated WorkflowData AnalysisSQLData Extraction

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.

app.dtdigital.it/data-report/pipeline● Running

Data automation · Python

Reports generated5every day at 06:30

Rows extracted3.200+ 3 CSV files

Checks passed5/72 errors avoided

Time per report4mwas 2h manual

Run #6 · DB extract20% pipeline complete

SQLCSVCheckExcelOutput

DB extract | Connection and SQL query

Cross-checks5 checks passed

Check	Sources	Result
DB vs CSV sales totals	DB ↔ CSV	Waiting
Duplicate customer codes	CSV ↔ CSV	Waiting
Consistent VAT rates	DB ↔ CSV	Waiting
Dates within report period	CSV ↔ CSV	Waiting
Prices vs 2026 price list	DB ↔ CSV	Waiting
Per-branch sums	CSV ↔ CSV	Waiting
Negative amounts	DB ↔ CSV	Waiting

2 errors avoided: flagged in the Anomalies sheet before the report is sent

Live logreport.py

06:30:00SQL → 3,200 rows extracted422ms

report_ottobre_2026.xlsx · 4 sheetsPending

Summary24 rows

Sales detail3200 rows

DB-CSV comparison1184 rows

Anomalies37 rows

Time saved

Manual2hAutomated4mfor 5 generated reports

Key results

Time cut from hours to minutes

Human errors eliminated

Structured, ready-to-use reports