Vasanth Kanapala — Data, Analytics, and Quality Engineering
Design and operate enterprise data, analytics, and quality engineering systems with a focus on reliability, traceability, and production readiness.
My work spans the full lifecycle of modern data platforms — including ingestion, SQL-first modeling, BI consumption, data quality enforcement, and GenAI / ML workflow validation in large-scale, production environments.
Engineering Focus
Data & Analytics Engineering
- SQL-first data modeling using SQL Server and MySQL
- Incremental ingestion pipelines with deterministic key strategies
- Analytics-ready schemas optimized for performance and downstream BI
Business Intelligence & Analytics
- Power BI dashboards with source-traceable, validated metrics
- KPI reconciliation across Excel, SQL, and BI layers
- Analytics aligned to operational and financial decision-making
Quality Engineering & Reliability
- Production-grade data quality frameworks with exception auditing
- Referential integrity enforcement across distributed data systems
- Release validation and regression safety for analytics pipelines
GenAI / ML Quality Engineering
- Validation strategies for GenAI and ML-assisted workflows
- Drift detection, consistency checks, and human-in-the-loop review patterns
- Quality assurance approaches for AI-augmented enterprise systems
Delivery & Governance
- Agile, sprint-based delivery with documented increments
- Documentation-driven design and change traceability
- Release readiness supported by validation evidence
Featured Projects
Retail Inventory Integrity & Revenue Assurance
https://github.com/kanva001/Retail-Inventory-Integrity-Revenue-Assurance
Enterprise analytics and data quality platform addressing inventory drift,revenue leakage, and KPI integrity across retail systems.
GenAI QE Enterprise Lab
https://github.com/kanva001/genai-qe-enterprise-lab
Quality engineering framework for validating GenAI and ML workflows, focusing ondrift detection, consistency, failure modes, and human-in-the-loop controls in
enterprise AI systems.
RetailOps Intelligence Platform (ROIP)
https://github.com/kanva001/RetailOps-Intelligence-Platform
Layered analytics architecture separating ingestion, modeling, and BI consumption with built-in validation, auditability, and performance awareness.
Current Focus
- Strengthening SQL-first KPI pipelines and validation logic
- Advancing production-ready data quality and QE frameworks
- Expanding GenAI and ML quality assurance patterns for enterprise workflows
Contact GitHub: https://github.com/kanva001