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Deployed

Azure ETL Pipeline

Scalable data processing pipeline using Microsoft Fabric and SQL to automate Azure financial cost analysis, transforming a 13-step, 2-3 hour monthly process into a 5-10 minute workflow.

Microsoft FabricAzure Data FactorySQLAzure FunctionsPythonPower BI

Process Transformation

Before: Manual Process

  • 13-step manual Azure cost analysis process
  • Required 2-3 hours of an engineer's time monthly
  • Error-prone manual data collection and calculations
  • Inconsistent reporting timing and formats

After: Automated Pipeline

  • Automated pipeline completes analysis in 5-10 minutes
  • Zero manager involvement in routine operations
  • Reliable, consistent data processing with validation
  • Standardized reporting with automated delivery

Technical Implementation

Data Extraction & Processing

Built automated system using Microsoft Fabric to extract Azure billing data and SQL for complex transformations, handling cost categorization and departmental allocation with built-in validation and error handling.

Microsoft FabricSQL TransformationsData Validation

Automation & Monitoring

Implemented monthly scheduling with comprehensive monitoring and recovery capabilities. Responsible for ongoing pipeline maintenance, database recovery, and continuous enhancements.

Azure FunctionsScheduled ExecutionRecovery Procedures

Key Achievements

Achievement 1

Reduced data processing time by 95% (2-3 hours to 5-10 minutes)

Achievement 2

Eliminated manual effort for managers with automated reporting

Achievement 3

Built fault-tolerant pipeline with ongoing support and recovery capabilities

Achievement 4

Delivered highly reliable, repeatable results for financial analysis

Project Scope & Responsibilities

Development & Implementation

  • End-to-end pipeline architecture and design
  • Microsoft Fabric workspace configuration
  • SQL query optimization and data modeling
  • Error handling and monitoring implementation

Ongoing Support

  • Monthly pipeline monitoring and execution
  • Database recovery and backup procedures
  • Continuous enhancements based on business needs
  • Performance optimization and scaling

Business Impact

Transformed manual Azure cost analysis into an automated, reliable workflow, saving managers hours of work monthly

95%
Time Reduction (2-3 hours → 5-10 minutes)

Operational Benefits

  • • Eliminated manual effort for managers
  • • Improved data accuracy and consistency
  • • Enabled reliable monthly financial analysis
  • • Reduced risk of human error in calculations

Technical Achievements

  • • Transformed 13-step manual process into automated workflow
  • • Built resilient system with recovery capabilities
  • • Delivered highly reliable, repeatable results
  • • Presented solution at company sprint reviews

Project Timeline

May 2025 - Present
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© 2025 Pryce Tharpe