A collection of automation tools designed to streamline recurring reporting workflows by collecting, validating, transforming, and distributing data with less manual intervention.
Python
SQL
Power Automate
Azure
Business Problem
Recurring reports were assembled by hand each cycle, consuming analyst time and introducing errors.
Solution
A set of Python and Power Automate utilities that collect, validate, and distribute reporting outputs on schedule.
Requirements
Scheduled extraction from multiple sources
Validation rules with failure alerts
Automated formatting and distribution
Run history and auditability
Architecture
Python scripts for extraction and transformation
SQL staging with validation queries
Power Automate for distribution and alerting
Cloud scheduling with logged run history
My Role
Documented the manual processes and failure points
Designed the automation and validation strategy
Developed and deployed the tooling
Monitored runs and iterated on feedback
Challenges
Designed workflows to handle upstream source changes and data-quality issues without silently producing incorrect outputs.
Built validation, logging, and failure alerts into the process so users could trust automated reporting outputs.
Lessons Learned
Made logging and validation part of the automation from the beginning, making failures easier to identify and troubleshoot.
Designed automated workflows with clear ownership and maintainability in mind rather than treating them as one-time scripts.
Business Impact
Reduced manual effort required to prepare and distribute recurring reports.
Improved reporting consistency by applying repeatable validation and transformation rules.
Converted repetitive reporting processes into scheduled, auditable workflows.
