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Built-In Calibration Standard and Decision Support System for Controlling Structured Data Storage Systems Using Soft

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Summary
This summary is machine-generated.

Selecting the right database management system (DBMS) is crucial for applications. This study introduces a decision support system (DSS) to streamline DBMS selection, saving time and resources.

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Area of Science:

  • Computer Science
  • Information Systems Engineering

Background:

  • Choosing an appropriate Database Management System (DBMS) is complex, requiring thorough evaluation of information access and professional judgment.
  • Companies face challenges integrating new technologies like cloud computing and advanced data management platforms.
  • The specialized nature of computer engineering necessitates tools to aid technology selection.

Purpose of the Study:

  • To present a Decision Support System (DSS) designed to assist non-experts in rapidly identifying suitable DBMS solutions and data retention strategies.
  • To provide a structured framework for evaluating and selecting optimal information architectures for software development.

Main Methods:

  • The proposed DSS utilizes the MoSCoW method for criterion weighting and assessment frameworks to quantify qualitative features based on industry expert knowledge.
  • Employs ISO/IEC qualitative features to establish links between criteria, informed by specialist expertise.
  • Integrates example reports and expert opinions to validate the selection process.

Main Results:

  • The DSS enhances visibility into the selection process, offering a more prioritized range of choices compared to individual research.
  • Demonstrates improved efficiency in selecting appropriate information architectures.
  • Reduces the time and cost associated with the decision-making procedure.

Conclusions:

  • The developed DSS effectively aids in selecting the most appropriate information architecture.
  • This approach offers a significant advantage over traditional, individual research methods for DBMS selection.
  • The system provides a deeper, prioritized selection range, saving users considerable time and expense.