Swift Services Company Database Remodeling

Swift Services Company Database Remodeling

Solution Framework

2.1 Solution Identification

To correct the problem of inconsistent and erroneous reports, Swift Services should have its database reviewed. This would identify the areas that require remodeling. For example, primary keys, attributes, and relationships could be remodeled appropriately (Ribeiro, Silva & Silva, 2015). The database entities would be checked to ensure that they have primary keys that are correctly referenced as foreign keys for proper relationships. As a result, data redundancy within tables would be eliminated, and records would be correctly linked between tables facilitating accuracy in system reports.

The process of fault identification and remodeling would involve obtaining the entity-relationship diagrams for the current database. This would include conceptual, logical, and physical models (Ribeiro et al., 2015). Then, based on the inconsistent reports, system users such as the staff at Swift Service would point out what is required from the reports. Comments from system users would be treated as database requirements that create database specifications documents (Ribeiro et al., 2015). The database specification document is important because database developers use it as a reference when designing a database. Also, the same document could be used later when a company grows and needs to scale up its system.

2.2 Hypothesis Statement

Evaluating the database at Swift Services would help in identifying the areas that require remodeling, hence, solving the various issues on system reports.

2.3 Research Questions

How will database remodeling help in correcting reports’ inconsistencies and errors in the Swift Services Company’s system?

2.4 Related Works

Poor database modeling has been found to be the root cause of inconsistent and erroneous reports as well as other system problems. For example, the GenBank, EMBL, and DDBJ databases have been reported to have redundancy and inconsistency as a result of poor database modeling (Chen, Zobel & Verspoor, 2017). The databases are used for research purposes but are found to be inefficient because of imperfectly modeled entities. This means that some records are updated more than once in the database, which makes it confusing when pulling reports (Chen et al., 2017). Duplication in databases is mainly a result of non-defined primary keys that also affect entity relationships because primary keys affect foreign keys (Ribeiro et al., 2015). Duplication also affects the quality of data stored in a database, hence the inconsistent and erroneous reports (Chen et al., 2017). Through research and experiments, Chen et al. (2017) proved that duplication of records in the GenBank, EMBL, and DDBJ could be eliminated by remodeling. They proposed that entities in the databases be reevaluated by ensuring that they are correctly named. Also, the database entities would require that attributes be correctly stated, and primary and foreign keys be properly configured. Chen et al. (2017) proposal is similar to the database remodeling proposed for Swift Services company.

The second case of proper database modeling was observed in an online voting system as a school project (Letkowski, 2015). Poor entity naming resulted in inconsistencies in voting results. This is because some records would be stored in unintended entities, which resulted in data omissions on reports. Therefore, the online voting project was unsuccessful. However, after properly renaming the entities and creating meaningful relationships between the entities, the database served its intended purpose (Letkowski, 2015). For example, the candidate and member entities were renamed and entities revised. This ensured that a candidate was not listed more than once in the database and that a candidate’s details, such as name and position, were accurate. In the member entity, a primary key was defined for the member ID, ensuring that each member had only one ID. This implemented measures ensuring that a member could only vote once. The voting data would then be stored correctly in respective entities, making it easy to see the voting progress from system reports in real time.

According to research by Bellatreche, Valduriez, and Morzy (2018), companies that deal with huge customer data keep remodeling their databases. This is because databases have to be scaled up whenever the company grows. An increased customer base is directly related to company growth. Unless a company handles humongous data, it can still use relational database management systems that require database modeling and remodeling (Bellatreche et al., 2018). This is exceptional for companies with humongous data that would be more suitable to use big data technologies. For example, companies such as Walmart started with relational database management systems and had to remodel their database when they encountered growth to maintain data quality (Bellatreche et al., 2018). However, the company transitioned to big data technology after reaching the humongous data point. Swift Services does not deal with humongous data; therefore, it can still use relational database management systems. This makes the database remodeling option suitable for Swift Services company.

The three research cases discussed here prove that the database remodeling proposal for Swift Services company would be ideal in solving the inconsistent report issue. This would require that the current ERD diagram is reevaluated in tandem with user feedback and the database be remodeled iteratively.

References

Bellatreche, L., Valduriez, P., & Morzy, T. (2018). Advances in Databases and Information Systems. Information Systems Frontiers volume, 20, 1-6. Retrieved from https://link.springer.com/article/10.1007/s10796-017-9819-2

Chen, Q., Zobel, J., & Verspoor, K. (2017). Duplicates, redundancies, and inconsistencies in the primary nucleotide databases: a descriptive study. Database (Oxford), 163. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5225397/

Letkowski, J. (2015). Doing database design with MySQL. Journal of Technology Research, 1-15. Retrieved from https://www.researchgate.net/publication/271910489_Doing_database_design_with_MySQL

Ribeiro, A., Silva, A., & Silva, A. (2015). Data Modeling and Data Analytics: A Survey from a Big Data Perspective. Journal of Software Engineering and Applications, 8, 617-634. Retrieved from https://www.researchgate.net/publication/288872507_Data_Modeling_and_Data_Analytics_A_Survey_from_a_Big_Data_Perspective

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The definition of your problem should now be completed, and you should be ready for the research phase. This is a key step in the research process and should result in meaningful, measurable, and useful information that you will use later for analysis purposes. Proper execution of your research plan will play a large role in the success of your project.

For this assignment, you will continue (FROM THE IP1 ASSIGNMENT) your work on the project with a focus on identifying a solution that can address the root cause of the problem. You will first select the suited framework which will guide you to develop the solution. Then, you will define the specifics of the solution and put it into a one-sentence hypothesis statement. After carefully studying both the problem statement and the hypothesis statement, you will extract a pair of important concepts reflected in the two statements. A research question can be formulated based on these two concepts. You can also use these two concepts qualified with the problem subject area as the search keywords to find some references that report similar research works completed by other researchers. After evaluating these references, you need to find out the main differences between those research works and the solution that you have proposed. All of these will be written into the corresponding sections of the Template of the Content of the Computer Science Problem-Solving Research Project Report document and will be presented as part of the submission for the week.

The following are the PROJECT DELIVERABLES:

Update the previously completed sections based on related feedback.
New Content for Week 2:

2. Solution Identification
2.1 Solution Framework
Based on the nature of the root cause of the problem, discuss what computer science principles, models, concepts, algorithms, platforms, etc., should be applied in order to develop a proper solution to address the root cause of the problem. This part is considered as the theoretical foundation of the solution.

2.2 Hypothesis Statement
Based on the Solution Framework, you will define the specifics of a solution that can be applied to resolve the root cause of the problem. Because this solution is only an assumed solution, it will be treated as a hypothesis at this stage of the research. You need to formulate a one-sentence hypothesis statement in the format of “If the solution is implemented, then the root cause of the problem will be resolved”.
For example, to solve the problem of the darkness in the classroom due to a sudden power outage in the evening, which is described by the problem statement, “In the campus, all classrooms are now embedded in the darkness due to the sudden power outage”, an assumed solution could have several possibilities: such as finding an electricity generator powered by either diesel or man-power or finding some pre-charged batteries for lightening, etc. Therefore, the corresponding one-sentence hypothesis statement can be written as: “If we can find any of the following: an electricity generator powered by either diesel or man-power or even some pre-charged batteries for lightening within the campus, we can effectively resume the classes.” From this hypothesis statement we can see clearly what solution has been proposed in order to address or resolve the root cause of the problem: “the sudden power outage”.

2.3 Research Questions
Based on both the problem statement and the hypothesis statement, you should find a pair of important concepts reflected in these two statements. Then, you will treat one of the concepts as an Independent Variable and the other concept as a Dependent Variable. Then, these two variables will be used to formulate a research question in the format of “How will the values of the Independent Variable changes impact the outcome of the Dependent Variable?” This research question will become the guideline for designing research experiments in the next step of the research process.
For example, we can easily extract two concepts: “Type of Electricity Generator” and “Effectiveness of Electricity Generating,” by evaluating the problem statement and the hypothesis statement. We will use the “Type of Electricity Generator” as the Independent Variable as it can have at least three possible “values”. We will also use the “Effectiveness of Electricity Generating” as the Dependent Variable. Therefore, we can have the research question defined as: “How will the values of the type of electricity generator change impact the outcome of the effectiveness of electricity generation?”
As you can now easily see, to answer this research question, all we need to do is experiment by trying each type of electricity generator and measuring the corresponding effectiveness of their electricity generation. That is, the research question, in fact, has provided clear guidance on how to design the research experiments.
2.4.Related Works
By using the Independent Variable and Dependent Variable plus the subject area of the problem as the search keywords, you can easily find some research works that are relevant in the publications. These publications should be used as references for you to investigate the differences in details between the solutions that you have chosen. You should select at least 5 such references, and make a short summary for each reference. The summary should point out the main technical features, the pros and cons of the research work, and the main difference between your solution and the other.
For example, if we use “Electricity Generator” or “Effectiveness of Electricity Generating” or “Solution for Electricity Recovering during Sudden Power Outage” as the search keywords to find similar research works, we should be able to find many references that discuss the solution similar to what we are researching.
After collecting the relevant references, all we have to do is to first classify them into categories, then make a summary of the main technical features, the pros and cons of each category of solution, as well as the main difference between each category of solution and your solution. These summaries become the content of the Related Works section.