Effective database design is very important for organizations to ensure efficient storage, retrieval, and management of data. Properly the fundamental concepts of database design and modeling bring many benefits such as data organization, integrity, performance optimization, scalability, and data security. The retail industry generates vast amounts of data from various sources, including sales transactions, customer interactions, inventory management, and marketing campaigns. Efficient database design is crucial for retail businesses to handle this data effectively, derive meaningful insights, and improve decision-making processes. Next, I will discuss in more detail the necessity of following the fundamental concepts of database design focused on fresh retail business.
Data structure complexity:
In the fresh retail project, the data is very complex and need a well-designed database that ensures efficient storage and organization of data. It helps in avoiding data duplication and inconsistency, making it easier to retrieve and update information.
In the paper by Chudinov [2], the author proposed a methodology that comprises three stages: analysis of needed information, defining initial entities, and normalizing the relation of entities. By applying this methodology, fresh retail businesses can effectively identify the core entities relevant to their specific domain. This involves understanding the different types of data entities (such as meat, fish, eggs, vegetables, fruits) and their attributes. By analyzing the specific requirements of the business, seasonal variations, geographic considerations, and religious preferences, the entities, and their properties (following the paper of Le [3]) can be defined in a comprehensive manner. Taking the example of Bachhoaxanh.com, one of the popular fresh retail companies in Vietnam, the understanding of specific data entities, their attributes, and their relationships through the analysis stage can greatly contribute to the design and implementation of a well-structured database.
Data Integrity and Consistency:
Designing the database needs defining constraints, data types, and validation rules to ensure data integrity and quality. These components play a crucial role in maintaining the accuracy, consistency, and reliability of the data within the database. As Microsoft[6] and GoSparker [7] mention, by defining appropriate validation rules, the database can detect and prevent the entry of inconsistent, inaccurate, or invalid data. Different from other retail domains, fresh retail provides many kinds of food in the same category such as bananas. The prices of food also change by day or season. Therefore, a unique identifier for products, prices, or transactions is important. Primary key constraints ensure that no duplicate records are entered and provide a reliable way to identify and retrieve specific data. In addition, data types should be assigned to ensure accurate representation and efficient storage of information.
Scalability and Flexibility:
The retail industry often deals with a huge volume of data, including product information, sales transactions, customer data, inventory records, and more. As the business grows, the database needs to be able to handle the increasing data load and adapt to changing business requirements. In [6], Watt provides many classifications of systems which can apply to the database of fresh retail organizations such as Centralized systems or Distributed database systems. A centralized system may be more suitable for smaller retail organizations with relatively simpler data management needs and a limited number of users. On the opposite, a distributed database system is typically preferred for larger retail organizations that require scalability, performance, and fault tolerance.
All in all, effective database design is crucial for fresh retail businesses to handle the complexity of data, maintain data integrity and consistency, ensure scalability and flexibility, and enhance data security. By following the fundamental concepts of database design, such as identifying entities and their attributes, defining constraints and validation rules, optimizing performance, and choosing scalable database architectures, fresh retail businesses can effectively store, retrieve, and manage their data.
[1] Learn DBMS: Simply easy learning. (2021). Tutorialspoint. https://www.tutorialspoint.com/dbms/index.htm
[2] Chudinov, I. L., Osipova, V. V. & Bobrova, Y. V. (2017). The methodology of database design in organization management systems. Journal of Physics: Conference Series, 803(1). IOPscience. http://dx.doi.org/10.1088/1742-6596/803/1/012030
[3] Vo, L. T. H., Thien, H T., & Nassif, A. (2023). Customer satisfaction with a named entity recognition (NER) store-based management system using computer-mediated communication. In H. P. Bui, & R. Kumar (Eds.), Multidisciplinary Applications of Computer-Mediated Communication IGI Global. https://doi.org/10.4018/978-1-6684-7034-3.ch013, https://doi.org/10.4018/978-1-6684-7034-3
[4] Watt, A., & Eng, N. (2014). Chapter 5: Data modeling. In Database Design, 2nd Edition. Opentext. Licensed under CC BY 4.0. https://opentextbc.ca/dbdesign01/
[5] Watt, A., & Eng, N. (2014). Chapter 6: Classification of database management systems. In Database Design, 2nd Edition. Opentext. Licensed under CC BY 4.0. https://opentextbc.ca/dbdesign01/
[6] Database design basics. (2021). Microsoft. https://support.microsoft.com/en-us/office/database-design-basics-eb2159cf-1e30-401a-8084-bd4f9c9ca1f5
[7] GoSparker. (2016, January 10). Database design tutorial [Video]. YouTube. https://www.youtube.com/watch?v=I_rxqSJAj6U&t=40s