Krupal Gangapatnam is a seasoned SAP Cloud Architect and certified technical consultant with over 15 years of experience in SAP Basis and HANA, specializing in installations, upgrades, migrations, and cloud infrastructure administration. He has a robust track record of leading end-to-end SAP S/4HANA implementations, Fiori configurations, kernel upgrades, and the integration of innovative solutions for enhanced system performance and compliance. Krupal holds multiple SAP certifications, including SAP S/4HANA Conversion and System Upgrade, HANA 2.0, and SAP Activate Project Management. His technical acumen extends to cloud platforms such as AWS, Azure, and GCP, where he has successfully executed complex SAP migrations and high-availability configurations. Notably, he has played key roles in projects with Ingram Micro and Johnson & Johnson through LTI Mindtree, where he drove real-time data replication, enterprise system upgrades, and disaster recovery strategies. A critical member of SWAT (L3) teams, Krupal is known for his expertise in resolving high-priority issues, advising on enterprise architecture, and ensuring data privacy through PII anonymization across SAP systems. He holds a Master?s degree in Computer Science from JNT University, Hyderabad, and is fluent in English with basic proficiency in Japanese.
Krupal Gangapatnam?s research interests include SAP S/4HANA migrations, cloud-based ERP infrastructure, and system performance optimization. He is also focused on data privacy, DevOps integration, and high availability solutions within SAP environments.
This article explores the design and deployment of AI-driven, adaptive, and automated data anonymization frameworks across mainframe, SAP ERP, and cloud platforms. It addresses pressing data security challenges and outlines the core anonymization techniques enabled by intelligent automation.
The study emphasizes platform-specific considerations, highlights the efficiency gains from AI integration, and examines the role of real-time monitoring systems. Findings demonstrate that AI-enhanced anonymization significantly improves data protection, regulatory compliance, and operational scalability across diverse and complex IT environments.