Ayush Rajora

This project focuses on analyzing and transforming data gathered from a website, establishing real-time metric tracking capabilities

• Conducted website analytics to understand top Traffic Sources, Path Vectors, and Conversion Rates for informed decision making contributing to a 3% increase in conversion rates
• Developed Dimension Tables, Data Models by employing Advanced Transformation Techniques in SQL for complex query building, enhancing efficiency in organizing unstructured data
• Automated job scheduling and monitoring using Python, increasing Operational Efficiency by 20% and streamlining processes for optimal performance
• Optimized SQL query execution, reducing complexity by 20-30%, resulting in significant cost savings and more efficient resource utilization
• Developed an end-to-end funnel and integrated various business metrics on Tableau, enabling real-time tracking without manual interventions and errors.

It’s a modernization project aimed at transforming a legacy production warehouse management application for the world's largest brewer. The project involved migrating the existing application to a more modern architecture. The project's objective was to enhance operational efficiency and data management using micro services-based architecture

• Enhanced PWM application efficiency by analyzing VB6 and C# legacy code, migrating to Angular Frontend, and implementing a .NET backend on Azure, ensuring a smooth transition and improved performance
• Collaborated across Teams to comprehend legacy system's data structures, relationships, and business logic
• Devised robust migration processes, guaranteeing Accuracy by implementing Data Cleansing and Validation procedures, and seamlessly integrated with SQL Server for enhanced data management and efficiency
• Facilitated smooth transition, extracting insights through Knowledge Transfer Sessions
• Resolved data discrepancies, achieving 99% Accuracy in collaboration with QA teams
• Designed and developed Complex Tableau Reports, aiding data-driven decisions for stakeholders
• Improved application functionalities based on profound Insights Derived from the analysis of legacy data.