Dheeraj Bansal is a seasoned Program Manager, Data & AI Delivery Leader, and Enterprise Analytics Architect with over 17 years of experience driving large-scale digital transformation, data modernization, and AI-enabled analytics initiatives across global organizations. Currently serving in leadership roles supporting Levi Strauss & Co.'s global retail ecosystem, Dheeraj oversees enterprise-scale analytics platforms, cloud transformation programs, and AI-driven reporting solutions that support mission-critical business operations. He has successfully led modernization initiatives involving SAP BW/HANA, SAP S/4HANA, Google BigQuery, Looker, Tableau, and advanced data governance frameworks, enabling organizations to improve decision-making, operational efficiency, and business resilience. Throughout his career, Dheeraj has held key leadership positions with leading multinational organizations including Levi Strauss & Co., Lexmark International, Cardinal Health, Wipro, Cognizant, and Tech Mahindra. His expertise spans Data & AI Strategy, Cloud Analytics, Business Intelligence, Enterprise Architecture, Data Governance, Digital Transformation, Supply Chain Analytics, and Program Management. Dheeraj holds a Master of Science in Computer Software Engineering from Birla Institute of Technology and Science (BITS), Pilani, and a Bachelor of Technology in Computer Engineering. He is the recipient of several professional recognitions and holds multiple certifications in SAP Analytics Cloud, SAP BW/4HANA, SAP Activate Project Management, Data Services, and Google Analytics. His research and professional interests focus on AI-powered analytics, enterprise data modernization, cloud-native intelligence platforms, governance-driven reporting architectures, and the future of data-driven business transformation.

 Title:Beyond Stability: Why Leading Retailers Are Moving from Traditional Data Warehouses to Cloud-Native Analytics Platforms Abstract:Retail businesses today need faster decisions, fresher data, and more flexible technology platforms. Traditional data warehouses have helped organizations for many years by providing reliable reporting, historical analysis, and governed business dashboards. However, modern retail now generates data from many more sources, including stores, e-commerce platforms, mobile apps, customer loyalty programs, supply chains, and digital transactions. Because of this growing volume and speed of data, many traditional warehouse architectures are reaching their limits. This presentation will discuss why leading retailers are moving toward cloud-native analytics platforms. It will explain how cloud platforms help retailers scale faster, process data closer to real time, support AI and machine learning use cases, and bring different types of data together in one modern analytics environment. The session will also cover important business drivers such as inventory optimization, customer personalization, supply chain visibility, faster decision-making, and self-service analytics for business users. The presentation will also touch on governance, security, data ownership, and migration strategy. The key message is that moving to cloud-native analytics is not only a technology upgrade. It is a business shift that helps retailers become more adaptive, more customer-focused, and better prepared for AI-driven decision-making.