Enabling Analytics Use Cases for a Large Fast-Food Company Using AWS and Databricks through POD based Operating Model

The fast-food industry generates massive amounts of data, which, when analyzed, can enhance decision-making in areas like supply chain optimization, customer personalization, and operational efficiency. This paper explores a cloud-based analytics framework using Amazon Web Services (AWS) and Databricks, tailored to meet the high-velocity needs of a large fast-food company [1]. By implementing a POD-driven operating model, teams focused on specific business areas and use cases and the company achieves modular, scalable, and agile data processing [2]. This paper discusses the architectural design, implementation, and effectiveness of the POD model in handling analytics use cases at scale, highlighting improvements in data pipeline efficiency, cost optimization, and agility.