AutomationData ProcessingDashboard
Automated Reporting Dashboard
Built an end-to-end automated reporting system that reduced manual data entry by 80% and improved reporting accuracy for a startup operations team.
2 min read
Project Overview
A startup company was spending over 20 hours per week manually compiling reports from multiple data sources. The leadership team needed real-time visibility into operations but was constrained by outdated spreadsheet-based processes.
The Challenge
- Multiple data sources: Sales, inventory, and financial data were scattered across 5+ platforms
- Manual consolidation: Team members spent hours copy-pasting data into Excel
- Delayed insights: Reports were often 3-5 days behind, making them less actionable
- Error-prone: Manual data entry led to frequent errors and inconsistencies
Solution Implemented
I designed and implemented an automated reporting pipeline that:
- Unified data collection - Connected APIs from Shopify, QuickBooks, and internal databases
- Automated ETL processes - Built data transformation pipelines using Python and Make.com
- Real-time dashboards - Created interactive Power BI dashboards with auto-refresh
- Scheduled reports - Automated daily/weekly email reports to stakeholders
Results
"This system transformed how we make decisions. We went from looking at last week's data to having real-time insights at our fingertips."
- 80% reduction in manual data entry time
- 99.5% accuracy in automated reports vs ~92% with manual entry
- Real-time visibility - Reports now available instantly instead of days later
- 20+ hours saved per week across the team
Technologies Used
- Python (Pandas, APIs)
- Make.com (Integromat)
- Power BI
- PostgreSQL
- REST APIs
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