Topic 2 DQ 2

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Maryville University *

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Information Systems

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Jan 9, 2024

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Effective database design is crucial for optimizing system performance and ensuring data integrity. The resource "Database Design Bad Practices: Are You Making Mistakes" sheds light on common pitfalls to avoid in development design (Martinez, 2017). To mitigate these issues in my own database design model, several key strategies can be implemented. Firstly, meticulous planning and requirement analysis are paramount. Understanding the specific needs of the application and the relationships between different data entities helps in creating a well-defined database structure (Martinez, 2017). This aligns with the best practice of avoiding inadequate requirements gathering, ensuring that the database design addresses the actual demands of the system. Normalization is another vital strategy. By organizing data to minimize redundancy and dependency, normalization enhances data integrity and reduces the risk of anomalies (Ullah & Mahmoud, 2022). It is essential to avoid the bad practice of ignoring normalization principles, as it can lead to inefficient storage and maintenance issues over time. Furthermore, enforcing data constraints and utilizing indexing judiciously can contribute to performance optimization. By adhering to data integrity constraints, such as primary and foreign keys, and carefully choosing which columns to index, the database design becomes more robust and responsive. Regular reviews and testing throughout the development process are crucial strategies (Chereja et al., 2021). This involves constant evaluation of the database design against evolving requirements and conducting performance testing to identify and rectify any bottlenecks or inefficiencies. In conclusion, to avoid the pitfalls highlighted in the resource, a comprehensive approach encompassing careful planning, normalization, constraint enforcement, indexing, and ongoing testing should be integrated into the database design process. These strategies collectively
contribute to the development of a robust and efficient database system, mitigating the risks associated with bad design practices. Chereja, I., Hahn, S. M. L., Matei, O., & Avram, A. (2021). Multidimensional analysis of NewSQL database systems. In  Software Engineering and Algorithms: Proceedings of 10th Computer Science On-line Conference 2021, Vol. 1  (pp. 221-236). Springer International Publishing. Martinez, F. (2017). Database Design Bad Practices: Are You Making Mistakes? Toptal. https://www.toptal.com/database/database-design-bad-practices. Ullah, I., & Mahmoud, Q. H. (2022). Design and development of RNN anomaly detection model for IoT networks.  IEEE Access ,  10 , 62722-62750.
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