# Effective Data Utilization in the Context of Industry 4.0 Technology Integration
## 1 Introduction  
Digitalization plays a key role in Industry 4.0 and has enabled a paradigm shift in industrial production through the synergy of the Internet and new technologies. The primary idea behind digitalization is the integration of isolated systems and the easy accessibility of data and information, which is expected to lead to faster data utilization in organizations. One of the ideas behind this Industry 4.0 concept is that by connecting machines, systems, and activities, organizations can create digital-intelligent networks across the value chain that will independently manage processes across the organizations and transform themselves into intelligent organizations [1, 2]. In their research, [PERSON] et al. [3] stated that digitalization enables the improvement and transformation of activities, functions, models, and processes in organizations and connects the real and virtual world of business through information and communication technologies. Driven by digitalization, Industry 4.0, and overall advances in cloud computing, IoT, Big Data, CPS and sensors, data are being generated at an unprecedented speed. Organizations must therefore look for new ways to extract value from these data and use it to give the organization a competitive advantage [4]. The authors of [5] suggested that the industrial organizations of the future will be more than just a system in which production with resources is interconnected and exchanges information. Intelligent industrial organizations will be managed by a fully integrated intelligent system that can manage the entire production system, anticipate problems before they arise and define the method and the time needed to solve them. They can be regarded as organizations that use smart manufacturing in alignment with Industry 4.0 technologies [6]. The Fourth Industrial Revolution is moving towards a complete change in the traditional manufacturing processes of organizations through the integration of Fourth Industrial Revolution technologies into already established manufacturing processes [7]. This revolution has also accelerated the integration of information technologies into manufacturing systems, and the data possessed by organizations are becoming increasingly sophisticated in terms of volume, variety and velocity [8]. Industry 4.0 focuses on intelligent processes within the production system, and these intelligent processes are enhanced by digital technologies such as IoT, Big Data, CPS and Cloud Computing providing continuous data collection and real-time monitoring of individual processes using sensors. This whole system of process monitoring, data collection and processing is mainly executed using the internet and transferring this collected data to large storage within the organization [9, 10]. Authors [PERSON] et al. [11] in their research stated that it is necessary to continuously combine real-time data flows from production to organization systems in order to autonomously respond to the results of predictive analyses. We agree with this idea and are further aiming to develop it in the context of Industry 4.0 as Industry 4.0 brings new solutions that should be flexible and efficient to cope with the increasing volume of data. [PERSON] also pointed out that these new technologies and solutions should be highly adaptable. The Industry 4.0 paradigm enables machines to communicate with each other and utilize all the data inside and outside the production processes. This approach allows machines and equipment to operate autonomously and efficiently. It also streamlines communication between machines and people, regardless of their location, and allows multiple devices to work interactively. Through these interactions, all participants in the organization's environment (suppliers, manufacturers and consumers) can obtain and collaboratively analyse data about products and the manufacturing and supply chain processes [12].