Investigation and designing a comprehensive supply chain database for Walmart

Abstract

In light of the rapid progression of digital technology, fierce competition, and the ever-shifting demands of consumers, the contemporary retail sector is continually evolving. This underscores the critical need to embrace digital solutions. This study seeks to aid Walmart, one of the world's largest retailers, in improving supply chain efficiency, optimizing inventory management, and enhancing the overall customer experience by creating a comprehensive supply chain database. Specifically, we employ the core entity method to identify Walmart's key entity, which is the "product," and ascertain its associated entities. Subsequently, we establish relational models based on the attributes and relationships of each table, considering real-world scenarios, such as one-to-many and many-to-many relationships. We employ normalization techniques to ensure the proper utilization of functional dependencies and candidate keys for each entity. This guarantees that the designed tables adhere to the principles of the First, Second, and Third Normal Forms, preserving data integrity while minimizing redundancy. Furthermore, we create a set of logical database commands, illustrated through flowcharts, and rigorously test their functionality and efficiency. Lastly, we explore potential directions for future research. The successful implementation of this design relies on robust data management practices and a reliable database system tailored to meet Walmart's specific needs. This results in a logically structured and standardized supply chain database. The research findings underscore the vital importance of a well-conceived supply chain database in addressing the challenges faced by large-scale retail operations like Walmart supermarkets.