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AIAutomationReportingFinance
AI-Based Reporting Automation
From hours of manual work to automated reports
Role:AI Engineer & Implementation Lead
Duration:6 months
>90%
Time savings per week
0
Manual errors
Real-time
KPI availability
The Context
A finance team spent significant time each week manually compiling KPI reports from multiple data sources. The process was error-prone, and by the time reports were ready, the data was often already outdated.
The Challenge
- 110+ hours per week spent on manual report compilation
- 2Data from 5+ different source systems
- 3Frequent errors in manual data aggregation
- 4Reports often delayed, reducing decision-making speed
The Approach
- 1Mapped all data sources and report requirements
- 2Built automated ETL pipelines with data quality checks
- 3Created AI-powered anomaly detection for KPI monitoring
- 4Implemented self-updating dashboards with scheduled alerts
Technologies Used
PythonSQLPower BIAzure Data Factory
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