Большие Данные и инструментарий для аналитики

Abstract

Проанализированы материалы известных зарубежных аналитических корпораций, исследовательских компаний в области ИТ и международных научных центров. Сквозь призму свойств и характеристик, природу и потенциальную ценность Больших Данных прослежено влияние на трансформацию ИТ к новому набору ключевых технологий, формирующих платформу обработки для извлечения новых знаний, обнаружения неочевидных связей и углубленного понимания, проникновения в суть явлений и исследуемых процессов.

Проаналізовано матеріали відомих закордонних аналітичних корпорацій, дослідницьких компаній в області ІТ, міжнародних наукових центрів. Крізь призму властивостей і характеристик, природу й потенційну цінність Великих Даних простежено вплив на трансформацію ІТ до нового набору ключових технологій, що формують платформу обробки для добування нових знань, виявлення неочевидних зв'язків і поглибленого розуміння, проникнення в суть явищ і досліджуваних процесів.

Introduction. The materials of the well-known foreign analytical corporations, the research IT-companies, and the international scientific centers are analyzed. The influence on transformation of the IT to a new set of key technologies creating the platform for their processing is traced through a prism of the properties and characteristics, the nature and potential value of Big Data. Purpose. It is important to create and research the methods and technologies for processing the Big Data for extracting new knowledge, discovering non-obvious links and in-depth understanding of the phenomena and the investigated processes and the prospects of their development. Methods. The informational and analytical methods and technologies for data processing, the methods for data assessment and forecasting, taking into account the development of the most important areas of the informatics and information technology. Results. Consolidated analysis, even with a small number of external data sources, is too expensive. Actually, creating a DB takes time and the significant resources for putting them into operation. In this regard, interest shifts from the traditional stores to hybrid and logical solutions. In a limited application it is possible to use a flexible approach aimed at reducing the dimension of the Big Data. The storages orientation for the widespread use in the intelligent analytical processing problems, with their inherent deep insight into the investigated phenomena, requires the simple access to all available types of the information resources, the possibility of using them in the different way, and the delivery of the required data to the application resources without their movement. Agreeing on the concept of the logical storage in general, we imagine the LDW storage as a loosely coupled, providing the necessary flexibility, multi-layered architecture, which includes new technologies and the progressive means of identifying, extracting and preparing a wide range of data. In this case, the analysis, taking into account the logic of the information processing, provides a certain information resource to the application as a service. This will ensure the simple availability and relevance of the information contained in the Big Data. Conclusion. Big Data is a complex inter-branch scientific and technical problem. In the future, the Big Data processing technologies, with the inclusion into its contours the methods and means of intellectualization, will be widely used in the economic, industrial and technological spheres and other important fields of human activity.