HARSHA KIRAN ADAPALA

– Analyze 10K+ support tickets per month using SQL, Excel, and data querying techniques to identify recurring issues, escalation patterns, and root causes, enabling structured problem classification across workflows. – Design and maintain 8+ interactive dashboards and automated reports in Power BI and Excel to track SLA performance, backlog movement, repeat issue frequency, and operational bottlenecks across queues. – Improve data quality across 5+ key case management attributes by implementing data validation checks, standardized tagging frameworks, and controlled input formats, ensuring reliable downstream reporting. – Develop and document 15+ detailed resolution playbooks, process workflows, and knowledge base articles, enabling consistent handling of recurring issues and reducing dependency on manual intervention. – Automate daily, weekly, and monthly reporting workflows using Python scripts and advanced Excel functions, reducing manual reporting effort by 20+ hours per month and improving data refresh consistency. – Support continuous improvement initiatives by analyzing multi-source operational data, contributing to standardization of workflows, improved data consistency, and reduced case duplication across systems.

– Designed AWS-based data pipelines using Redshift, S3, and Lambda to ingest, process, and store 10M+ rows of data per month, improving data availability and reducing query execution time by 25+ seconds per run. – Developed and delivered 25+ interactive dashboards and reporting solutions in Tableau and Power BI, supporting 5+ teams with tracking of customer retention, cart abandonment, SLA adherence, and operational KPIs. – Built and evaluated predictive models using Python, R, and Scikit-learn on logistics and fulfillment datasets covering 3+ warehouse operations, enabling improved shipment planning and inventory tracking. – Implemented data validation rules and quality checks across 15+ critical datasets using advanced SQL techniques such as CTEs, window functions, and stored procedures, ensuring accuracy in reporting outputs. – Collaborated with data engineering and analytics teams across 4+ cross-functional projects to support deployment of real-time anomaly detection workflows, improving monitoring of high-volume transactional data. – Mentored 3 junior analysts through 10+ structured training sessions and code reviews on SQL optimization, data visualization, and analytical techniques, improving team capability and delivery consistency.

– Designed and maintained 8+ ETL pipelines using SQL, Python, Excel Macros, and Informatica to process 5M+ records per month, ensuring consistent and reliable data ingestion for critical business applications. – Optimized complex SQL queries on datasets exceeding 1M+ records using CTEs, window functions, indexing, and stored procedures, reducing execution time by 20+ seconds per query and improving system performance. – Performed data cleaning, validation, and exploratory analysis on 3M+ structured and unstructured records, identifying inconsistencies and ensuring high-quality datasets for reporting and analysis. – Collaborated with 5+ cross-functional teams including business, operations, and technical stakeholders to gather requirements and convert them into structured data solutions and reporting outputs. – Orchestrated data governance practices across 10+ datasets, including standardized data definitions, metadata documentation, and validation checks, ensuring consistency and compliance in reporting. – Migrated 30+ legacy reports from Excel and SQL-based systems to Power BI and Tableau dashboards, improving accessibility for 25+ stakeholders and minimizing reliance on manual report generation.