20+ Hours Saved Monthly
Reporting Automation Workflow
End-to-end reporting automation using SQL and Python eliminating manual report generation and saving 20+ hours per month.
PythonSQLApache SupersetRedash
20+ hrs
Time Saved
Automated
Reports
Daily
Frequency
Problem Statement
Analysts spent 20+ hours monthly on repetitive manual report generation, copying data and formatting outputs for stakeholders.
Architecture
Scheduled Python scripts execute SQL queries, process results, and push formatted outputs to Superset/Redash with email delivery.
Database
ClickHouse and MySQL analytical databases.
Solution
Automated entire reporting workflow from SQL extraction through Python processing to scheduled dashboard delivery.
Key Queries
- Scheduled KPI extraction queries
- Report formatting aggregation queries
- Historical comparison queries
Dashboards Built
- Automated weekly business review dashboard
- Scheduled KPI email reports
- Self-serve report generation portal
Business Insights
Freed 20+ analyst hours monthly
Standardized report formats and definitions
Reduced human error in reporting
Challenges
- Handling varying stakeholder report requirements
- Ensuring scheduled job reliability
- Managing report versioning
Future Scope
- Natural language report requests
- Dynamic report customization
- Slack/Teams integration
Features
Scheduled report generationAutomated email deliveryTemplate-based formattingError notification system