Introduction
The accuracy of the data analysis system depends on various factors, with the selection of the appropriate database design methodology being among the determinants of the process’s effectiveness. Each given data set requires the data analyst to use a database design methodology that is suitable to achieve the desired accuracy objective. To be better positioned to identify the right data set to use, the data analysis needs to understand the strengths and weaknesses of the various database design methodologies. The analysis of the functionality and feature of iterative, top-down, and bottom-up database design methodologies will reveal that the data analyst should match each of them with the appropriate data set to achieve the desired outcomes.
Top-down database design methodology
Under this design methodology, the data analysis starts with common or general ideas before moving to the specifics. Notably, the methodology requires one to start right form what the system needs before engaging the end-users to offer insight into what type of data they deed to store in the established system. Most noteworthy, when using the top-down database design methodology, the data analyst has to work backward through the system to determine the ideal data that should be stored in the database.
Strengths
The key among this methodology’s strengths is that it enables a fast decision-making process making it ideal when the time is limited. This is particularly important when time is limited. The other strength is that it minimizes the chaos when attempting to design a system all at once because of the complexity of designing and implementing an information system. The top-down database design methodology enables separate systems analysis teams to work in parallel using different subsystems, thus saving a lot of time and setting the foundation for the desired quality outcomes. Finally, the top-down database design methodology prevents systems from getting mired, making it ideal to use large organizations that run a wide range of data.
Weaknesses
The only weakness of the top-down database system is that it may lead to unsatisfactory results because the analysts and the end-users may miss important elements that help improve the system’s functionality when as they start to form the general to the specific ideas.
Bottom-up database Design Methodology
Under this design methodology, analysts start from specific details before moving to the general ideas. When using this system, the data analyst must inspect all the interfaces of the system to determine the appropriateness and accuracy of the reports, screens, and other forms therein. The analysis then works backward through the system to determine the ideal data stored in the database.
Strengths
The strength of the bottom-up database design methodology is that it enables the designer to promptly implement the critical modules, making it easy to use and effective. The other advantage is that the methodology is easy to use, and it can quickly get something working when in operation.
Weaknesses
The methodology’s weakness is that it often lacks the capacity to have a system that can withstand a drastic change in the data content. Besides, it requires more time to maintain and flesh it out a little more.
Iterative Database Design Methodology
This design methodology allows the data analysts to use a continuous incremental process where there is a continuous cycle of prototyping, testing, and adjusting the system from time to time to fit the data system changes. It is unique in that it enables the users and the data analyst to position the digital experience that is in line with the end-users’ needs.
Strengths
This methodology’s strength is that it provides robust user feedback, thus informing the designer of the ideal ways of adjusting it to achieve the desired effectiveness. Another strength of this methodology is that it enables the measurably improves usability by allowing the change if the system changes the needs of the end-users. Most importantly, the system is efficient and cost-effective as it minimizes the adverse effects of breakdown or data loss as the testing and improvement is a continuous process.
Weakness
The only weakness of the Iterative Database Design Methodology is that it requires skilled manpower and immense resources in the short run to keep changing and improving over time.
Conclusion
Identifying the right database design to us in an organization greatly helps set the foundation for improved efficiency. Each of the database design methodologies has unique features and functionality attributes. Understanding the effectiveness of each is important in guiding organizations to settle on the appropriate one to use. Form the strengths and weaknesses of the three methodologies, the Iterative Database Design Methodology Seems ideal to use in a dynamic business environment characterized with changes in the needs of the end-users.