Big data

Scientific research on engineering solutions for the integration of streaming and stored data flows remains insufficient, which complicates the implementation of endto- end analytics, reduces production process transparency, and limits timely response to deviations in technological parameters. The relevance of this issue is emphasized, and the development of a parametric model for integrating operational printing production systems with target Big Data platforms for analytical processing of Industrial Internet of Things telemetry flows is justified.

This paper analyzes the challenges, current limitations, and future prospects of database systems in modern information systems. Quantitative assessments indicate that NoSQL solutions can increase transaction processing speed by up to 40% compared to traditional SQL systems under high load conditions, while cloud-based architectures reduce maintenance costs by approximately 30% and improve system availability.

Purpose. The purpose of this study is to analyse the transformation of managerial paradigms in the gambling industry under the influence of digitalisation, Big Data technologies, and increased regulatory control. The study aims to determine how technological innovations, data analytics, and digital platforms affect managerial decision-making, operational efficiency, and risk management in modern online gambling ecosystems.

The article analyzes modern approaches to the use of data warehouses and data lakes in the construction of information technology platforms for smart regions. Data processing technologies in data warehouses and data lakes allow for the integration, storage, and analysis of large amounts of information generated by various sources, including operational transaction systems, IoT sensors, and other data received in real time.

Digital transformation of public services in the context of modern information systems and technologies is a relevant area of research, which is due to the growing demands of society for the quality and speed of public services. In the digital economy, artificial intelligence, machine learning and big data processing technologies play an important role, which can significantly increase the efficiency of public administration.

The rapid accumulation of information assets requires new approaches to their storage and protection. The article is devoted to the analysis of modern approaches to storing large volumes of data, taking into account their efficiency, reliability and security. Key technologies such as cloud platforms, local solutions and distributed storage systems are considered, as well as the features of their application.

In the context of critical challenges related to global warming and the necessity of reducing carbon footprint, the electric car sector is experiencing significant growth. This progress inevitably leads to the need for expansion and modernization of the charging station infrastructure. This article conducts a detailed analysis of how big data processing technologies can contribute to the optimization of this infrastructure’s use, the efficiency of charging stations, and the development of personalized services for electric vehicle users.

An analytical review of the development of Data Lakes and its application in various industries, as part of Big data concept solutions, was conducted. The available standard architectural solutions for the Data Lake organization are considered. Also, specialized areas that require different or additional aspects to solve the tasks, depending on the field of Data Lake use, are taken into account. For the proper organization of Data Lake, various data processing tools are used, including distributed data storage systems, semantic networks, and especially metadata.