The real world can be explained using a simulator or through representative models. Even though the components of real-world systems are far more complex, the systems modelling It helps you familiarise yourself with its processes. Therefore, to gain a better understanding of what systems modelling is, we invite you to read on
To begin with, let’s first clarify What are systems?: distinct entities comprising interdependent elements and parts which, in turn, are interconnected. Although a system can be understood as a whole, altering any one of its parts affects the others. Its purpose is the maintenance and preservation of a larger system.
Generally speaking, systems exhibit a consistent pattern of behaviour, which makes them predictable. Furthermore, their growth depends on the system’s ability to adapt to the environment in which it operates.
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What is systems modelling?
With these concepts clearly in mind, we can define What is systems modelling?. It is a widely used tool in the study of systems, consisting of a way of representing real-world phenomena with the aim of describing, explaining or better understanding them.
In simple terms, a system model It is a partial representation of reality that enables us to observe its elements, relationships and boundaries. Therefore, asking what systems modelling is involves analysing how a representation is constructed that is useful for studying a phenomenon without directly intervening in it.
For example, if we want to explain what a car is, we can draw a picture; it would be better still to take a photograph, or, even better, to build a three-dimensional model that includes all its parts and allows us to examine them individually and as a whole.
So the systems modelling enables the study of simple and complex phenomena through the system simulation.
Characteristics of systems modelling
Bearing in mind that the aim of systems modelling is to represent an aspect of reality, let us examine the aspects that characterise it.
- It is regarded as a technical activity.
- It serves scientific and educational purposes.
- It must be reasonably accurate.
- It bears a complete or partial resemblance to the systems, whether in terms of their appearance or the processes and relationships that constitute them.
Types of systems modelling
Clarified What is systems modelling? And having outlined some of its characteristics, let us now look at the ways in which it is classified.
Depending on the scope of the subject under study
Thus, there may be simulations of biological, economic, urban planning and political models, amongst others. One example might be the implementation of logistics distribution models in the business logistics. In this regard, the book *Modelling of Load Distribution Systems* by Rodrigo Garrido serves as a useful reference.
According to the presentation format
- Physicists, such as physical systems.
- Analytical tasks, such as those carried out using computers.
At this point, Contreras Montes’s work on the modelling of computer systems is relevant.
What is systems modelling used for?
Essentially, we model for three reasons:
- When seeking to understand processes.
- When one wishes to understand the dynamics or the way in which a system behaves in a particular way.
- When one wishes to analyse and assess problems that are not visible or comprehensible in reality in complex systems.
To understand What is systems modelling? It enables us to understand our reality. The development and evolution of humankind have been made possible through this kind of research. Therefore, its application in both scientific and social contexts enables us to continue to understand the ‘why’ and ‘how’ of aspects relating to existence.
Systems modelling and software modelling
In computing, the software modelling It follows the same principles: it defines system models to represent requirements, components, data flow and relationships before building or modifying a solution. The relationship between models and systems makes it possible to work with virtual systems, review system modelling and verify whether the system model maintains the consistency of the system model.
Systems modelling, data modelling and UML
In the field of computing, the systems modelling It is also linked to data modelling and visual representation tools such as UML. Data modelling enables the definition, analysis and organisation of the information required by a system, as well as the representation of how data is stored, related and processed within a database.
This process is usually underpinned by different levels of design: conceptual design, which provides a general representation of entities and relationships; logical design, which defines the data structure in detail; and physical design, which focuses on its implementation within a database management system. For this reason, when studying system models, it is also useful to understand how the data flow is organised and what role each element plays within the system model.
What is data modelling?
The data modelling It is an essential technique for managing and organising information within computer systems. It is a process by which define and analyse the data needed to support business operations and the strategic objectives of an organisation.
This practice involves the creation of visual models that represent how data is stored, related and processed within a database. Data modelling is crucial for the development of efficient and accurate systems that facilitate decision making and the execution of business processes.
There are several types of data models, each suitable for different needs and contexts. The most common include:
- Entity-relationship model: Used to design relational databases, it focuses on entities (data objects) and the relationships between them. It can be used to design a database for an employee management system, where the entities include employees, departments and projects, and the relationships define how these elements interact.
- Dimensional model: Popular in data modelling for business intelligence systems, this model organises data into dimensions and facts, facilitating analysis and reporting. It is ideal, for example, for an e-commerce company that needs to analyse sales, where the dimensions might include time, product, customer and region, whilst the facts would be the sales themselves.
- Hierarchical model: One of the oldest forms of data modelling, in which data is organised into a tree structure with parent-child relationships. An organisation could use this to manage its organisational structure, where each employee reports to a supervisor, and so on.
- Network model: Similar to the hierarchical model, but it allows for multiple relationships, making it more flexible but also more complex. Each type of model has its advantages and disadvantages, and the choice will depend on the specific needs of the project and the organisation. It is useful in complex systems such as telecommunications, where different nodes (such as switches and routers) are interconnected in multiple ways.
What is UML?
The Unified Modelling Language (UML), an abbreviation for Unified Modelling Language, is used in software development to represent systems using diagrams. Among the UML diagrams Among the most common, we find:
- Sequence diagrams: they enable you to visualise and understand the dynamics of a system whilst it is running. These diagrams depict the interaction between the system’s various objects over time, showing how they communicate with one another and how operations evolve as they are carried out.
- Use-case diagrams: a tool that provides a clear and concise representation of the interactions between a system and its external stakeholders, offering a high-level view of how users interact with the system to achieve their objectives.
- Class diagrams: They represent the system’s classes, as well as the relationships and inheritance structures between them. They thus provide a detailed snapshot of the system’s internal architecture, showing how the classes are organised, what attributes and methods they possess, and how they interact with one another.
Thus, the software modelling It broadens our understanding of systems modelling, as it enables us to anticipate requirements, identify relationships between components and represent complex systems prior to their implementation.
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