Big Data in Finance

The question of Big Data technologies, not only in the fi-nancial sector, but in general, is a logical pattern of techni-cal and scientific progress of the last decades. The change of paradigms has led to the fact that today’s managers and economists have to work not only with large volumes of infor...

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Bibliographic Details
Main Author: Andrey Bulgakov
Format: Article
Language:English
Published: National Research University Higher School of Economics 2017-03-01
Series:Корпоративные финансы
Subjects:
Online Access:https://cfjournal.hse.ru/article/view/6528/7409
Description
Summary:The question of Big Data technologies, not only in the fi-nancial sector, but in general, is a logical pattern of techni-cal and scientific progress of the last decades. The change of paradigms has led to the fact that today’s managers and economists have to work not only with large volumes of information, but also with new types of data. Process-ing the new format files allows managers to make more accurate and effective financial decisions. It is necessary to say, why these decisions are important for business. They make it possible to achieve the goals that modern organ-izations set for themselves: increasing the value of the enterprise, increasing investment attractiveness, improv-ing the quality of forecasting. This situation in a well-func-tioning world system has led to the emergence and devel-opment of new trends in education, in particular, in the field of education of financial professionals. Focusing on Russian achievements and Western researches of funda-mental and applied disciplines, it should be noted that the modern financier is increasingly integrated into the Big Data technology environment. He needs knowledge of the construction of wording of requests to manage compe-tently. For this, the skills of working with search programs, the use of search operators, work with search robots are important. At the theoretical level the future financier must study strategic, statistical, mathematical, systemic, stochastic, probabilistic and other types of analysis.
ISSN:2073-0438