Enabling Analytics Use Cases for a Large Fast-Food Company Using AWS and Databricks through POD based Operating Model
Author(s): Shreesha Hegde Kukkuhalli
Publication #: 2411098
Date of Publication: 01.08.2023
Country: USA
Pages: 1-6
Published In: Volume 9 Issue 4 August-2023
DOI: https://doi.org/10.5281/zenodo.14250556
Abstract
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.
Keywords: Cloud based analytics, POD operating model, AWS architecture, Databricks, Data lake and Data warehousing, machine learning, Customer analytics
Download/View Count: 132
Share this Article