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‌‌ Abstract

   The increasing complexity of engineering systems and the generation of huge volumes of data in the design, simulation, performance monitoring and maintenance stages have made effective data management and analysis a vital need in the engineering industries. In such circumstances, databases play a key role in optimizing engineering processes by providing structured mechanisms for storing, organizing and retrieving data.
   This article focuses on the concept of databases and related technologies and examines their application in engineering systems data analysis. The aim is to analyze the role of databases in enhancing modeling accuracy, improving data traceability and facilitating decision-making in engineering projects. In addition, the importance of structuring data to support advanced analytics, such as machine learning, statistical analysis and predictive modeling, has been considered.
 Materials and Methods:
   The research method includes a systematic review of scientific literature, analysis of the characteristics of relational and non-relational databases, and examination of their application in areas such as supervisory control systems (SCADA), intelligent manufacturing systems, computer-aided engineering design (CAD/CAE), and sensor data analysis. Several case studies are also reviewed to demonstrate the impact of an appropriate data structure on the quality of analyses.
Findings and Conclusions:
   The findings show that the targeted use of databases leads to significant improvements in processing speed, data integrity, and the ability to interpret analytical results. Modern databases such as NoSQL, graph databases, and cloud systems enable the management of large and heterogeneous data and pave the way for more complex analyses in engineering.  Finally, we can conclude that the use of databases is a basic prerequisite for implementing intelligent and data-based engineering systems.

Keywords: Database, Data management, Data analysis, Engineering systems, Engineering data, Data mining, Data integration

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