ПРИМЕНЕНИЕ BIG DATA ПРИ АНАЛИЗЕ БОЛЬШИХ ДАННЫХ В КОМПЬЮТЕРНЫХ СЕТЯХ

Abstract

The concept of Big Data includes the totality of all data sets, the total size of which is several times larger than the capabilities of conventional databases.it is also necessary to note the use of non-classical data processing methods. For example, in the management, analysis of information received, or simply storage. Big Data algorithms have emerged in parallel with the introduction of the first high-performance servers of their kind, such as the mainframe, which have sufficient resources required for operational information processing, as well as corresponding to computer calculations with subsequent analysis. The algorithms are based on performing series-parallel calculations, which significantly increases the speed of performing various tasks. Entrepreneurs and scientists are interested in Big Data, who are concerned with issues related to not only high-quality, but also up-to-date interpretation of data, as well as creating innovative tools for working with them. A huge amount of data is processed in order for the end user to get the results they need for their further effective use. Big Data enables companies to expand the number of their customers, attract new target audiences, and also helps them implement projects that will be in demand not only among current customers, but also attract new ones. Active implementation and subsequent use of Big Data correspond to the solution of these problems. In this paper, we compare the main types of databases and analyze intrusion detection using the example of distributed information system technologies for processing Big Data. Timely detection of intrusions into data processing systems is necessary to take measures to preserve the confidentiality and integrity of data, as well as to correctly correct errors and improve the protection of the data processing system.