# Effective Data Utilization in the Context of Industry 4.0 Technology Integration
## 1 Introduction
### Big Data
#### 1.5.2 Big Data Analysis  
Big Data offers a huge opportunity to transform the current manufacturing paradigm towards smart manufacturing. Big Data enables organizations to adopt data-driven strategies and to become more competitive [16].  
With the development of the Internet of Things, smart manufacturing is enabling the generation of vast amounts of data. Big Data was measured in terabytes in 2005, petabytes in 2010, exabytes in 2015 and zettabytes in 2020. This amount of data brings with it a range of challenges [8; 20; 27].  
The demands for efficiently extracting valuable information from such a large amount of data are constantly increasing. Data analysis techniques can be divided into the following categories:  
* System infrastructure;
* Analytical methods.
* System infrastructure focuses on preparing data for analysis, while analytical methods focus on how to extract useful information from the data [27].  
Continuous production processes, a multitude of sensors and real-time data and their efficient transmission determine the data's basic characteristic called as 3V, which are represented by [5; 8; 20; 27]:  
* Volume;
* Variety;
* Velocity.  
Big Data analysis can contribute to streamlining production planning and optimizing manufacturing processes. Information obtained from customer orders, the status of production equipment, production capacity, supply chain data, sales and available inventory can be analysed using Big Data analysis methods. Production plans can be created based on the outputs of these analyses, which also ensures the optimal configuration of production resources and processes for the execution of individual tasks. Big Data analysis contributes to the assessment of the optimality of technological processes, by analysing process data, including historical data, and individual relationships that arise within processes and technology parameters, thus ensuring increased productivity, quality and cost reduction [16].  
Big Data analysis is becoming an essential requirement for extracting important insights from data, which will enable industrial organizations to reduce their costs and increase their profits. Big Data analysis is based on the principles of extracting, validating, translating and exploiting data. It is an emerging field that focuses on making empirical predictions. Organizations that are data-driven use analytics in decision-making processes at all levels of the organization [19].  
[PERSON] et al. [19] concluded that industrial organizations are beginning to utilize Big Data analysis because of the following reasons:  
* Gaining control over the vast amount of data generated;
* Utilizing these data to support decision-making processes and increase productivity.  
Thanks to the use of digitization, Industry 4.0 and overall advancements in cloud solutions, IoT, Big Data, CPS and sensors, data are being generated at an unprecedented rate. Organizations must therefore look for ways to select from these data those that will be of value and through which the organization will gain a competitive advantage [4].