## 1 Introduction
The last functional area, which is currently gaining in importance and increasing the efficiency of design, manufacturing, control, and management processes, includes the use of mechanisms and solutions in Big Data, machine learning, artificial intelligence, and expert systems. The whole area requires the implementation of effective algorithms supporting decision-making processes. In this area, modeling and programming languages such as UML (Unified Modeling Language) [38; 39], various variations of the C language [40; 41], and, for some time now, more and more often Java and Python [42; 43] were used. Therefore, in this article, the authors have decided to refer to the possibility of using the relatively new Go language in the decision-making process in relation to Java and Python. Of course, this study is not an overview article. It does not include an analysis of the extensive range of performance of programming languages in the context of constantly evolving software engineering, as well as the needs of different sectors of the economy and the needs of potential customers. It should also be noted that in the past few decades of IT development, very many programming languages have been developed. However, few of them have gained satisfactory popularity, expressed by the number of people using them and applications created on their basis. Analyzing current trends, it can be concluded that in the area of data analysis, machine learning, and artificial intelligence, Java and Python have great use and interest among users. Therefore, the authors have attempted to compare them with the relatively new and increasingly commonly used Go (Golang) language in decision-making processes in the context of solutions used in Industry 4.0. Analyzing the needs of the area related to Industry 4.0, the authors pointed out the need to create programs characterized by high operation speed and low load on hardware resources. This state of the art results from the fact that many IT and automation systems supporting design and production processes have the character of closed systems with little possibility of expansion and modernization. Of course, considering the extensive range of application areas of this type of scenario in the industry, the focus was on a selected aspect. Namely, systems supporting decision-making processes in remote rapid prototyping systems based on decision trees take into account the measure of entropy as a heuristics to choose an attribute. The authors are aware of the fact that there are many methods and means, as well as mathematical tools and their implementation, supporting decision making processes. Since the authors take part in research and development work related to remote prototyping systems (the system is called iS Rapid, developed by InfoSoftware Polska Ltd., Rzeszow, Poland), they have relied on data from such a system. However, it should be noted that the results concerning the performance of individual programming languages are more universal and can potentially be used in the future to implement solutions. Mostly solutions supporting decision-making processes in the industrial infrastructure regarding the selection of tools for individual manufacturing tasks, the type, composition of manufacturing materials, and the choice of control and verification mechanisms for the design and production process. Indeed, there are many well-described and repeatedly verified algorithms for analyzing and exploring data used in the decision making process. There are also many publications about their effectiveness and possibilities [44; 45]. Therefore, in this publication, we focus on tools, mostly programming languages used for algorithmic and application implementation of these algorithms. Individual languages' properties may also improve the speed and, particularly, the data analysis process's computational complexity. In this respect, the programming solutions used have an essential role to play.