scholarly journals Features of Big Data market risk identification

2021 ◽  
Vol 2021 (1) ◽  
pp. 82-95
Author(s):  
Olena Shandrivska ◽  
◽  
A. Kyrylenko ◽  
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Effective Management ◽  
Data Confidentiality ◽  
Management Decisions ◽  
Market Participants ◽  
Significant Damage ◽  
Data Market ◽  
Big Data Technologies ◽  
High Level

The paper hypothesizes that the dynamic digitalization of the economy, based on the benefits of using Big data, accelerates the use in management and production processes of technologies offered by this market. However, it is noted that the acquisitions of the Big data market also exacerbate the socio- economic contradictions between countries with developed market economies and institutionally underdeveloped countries, which include Ukraine. The authors of the study proposed to identify the Big data market with such key indicators as total revenue, number of Internet users, losses of Big Data market participants from data leakage. Thus, the high rates of development of the Big data market in terms of growth of total market income in 8,03 times during 2011 — 2020 were witnessed. The main segments of the Big Data market (service segment, software segment and service segment) were identified. It is established that the largest share of the Big Data market is occupied by the services segment (37,5% in 2020). From 2021, the growth rate of the software segment is expected to exceed other segments of this market — hardware and services. The results of the analysis of the Big Data market by M. Porter’s five forces model show that the most important of the competitive forces in the market is a high level of competition, in which market participants are encouraged to focus on potential needs and expectations of their customers to strengthen bases of differentiation and clear positioning of the services. According to the results of the SWOT-analysis of the Big Data market, the following strengths were identified: business expansion due to the increase in the amount of information it owns; increasing the number of customer reviews through social networks; establishing strategic partnerships with suppliers, dealers and other stakeholders through the use of Big Data; permanent training of employees to maintain the competitiveness of organizations; established IT system of the enterprise, which promotes faster adoption of effective management decisions; high incomes due to effective management decisions, possession of market research results through Big Data technologies. The identified market opportunities are: population growth, which means an increase in the number of potential consumers and the amount of data collected; growth in the number of enterprises that implement e-commerce in their activities; growth of active consumers due to the integration of Big Data into social networks; increasing the share of automated processes, which helps reduce costs; growing popularity of IT specialization in universities; globalization of the economy, which allows companies to expand their activities to other countries. On the basis of identified strengths of the market and its capabilities, the following strategic directions of development are proposed: entry of enterprises into new markets due to market globalization and effective implementation of Big Data technologies; use of social networks to collect consumer data and involve them in Big Data processes; improvement of the e-commerce system of enterprises due to the capabilities of well-established IT systems of the enterprise with the capabilities of Big Data; reduction of product prices due to cost optimization and effective interaction with contractors. The results of the research allowed to identify the following main risks of the industry: destruction of data confidentiality; collection of false data, infringement of intellectual property of a third party, etc. The formed risk matrix indicates that the most significant risks of this market are the reduction of information security of the entity due to hacker attacks (probability of 50%, significant damage) and the destruction of data confidentiality (probability of 25%, significant damage). Qualitative interpretation of risks in the Big Data market allowed to characterize the impact of adverse factors of internal and external environments, namely: insufficient unreliability of cloud storage for data storage; high level of distrust of data carriers to companies using Big Data; high staff turnover in the market, etc. Assessing the risk of data loss due to hacker attacks allowed to identify it as a risk of a high level of importance (6 p.). Based on the obtained result, it is concluded that the activities of Big Data market participants are vulnerable to possible hacker intrusions and require more effective measures to ensure reliable data protection of enterprises and their customers.

scholarly journals CAPABILITIES AND LIMITATIONS OF BIG DATA IN MARKETING

2021 ◽  
Vol 8 (4) ◽  
pp. 16-20
Author(s):  
Natal'ya Diesperova
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Search Engines ◽  
Big Data Technologies ◽  
The Absolute

Using of Big Data increases the efficiency of solving of marketing tasks, including drawing up a portrait of a consumer and building communication with him, based on the analysis of information from social networks (Facebook) and search engines (Google). An assessment of the capabilities and limitations of these technologies showed that the use of Big Data doesn’t always provide the absolute best marketing solutions. Therefore, the use of Big Data seems to be justified in marketing only in a number of areas, directed by a professional marketer, for whom Big Data technologies are an effective tool that allows to prepare an analytical base for making creative decisions.

scholarly journals Big Data Analytics With Reference To Wide Variety of Domains

2019 ◽  
Vol 8 (10) ◽  
pp. 1100-1104
Keyword(s):  
Health Care ◽  
Social Networks ◽  
Big Data ◽  
Data Analytics ◽  
High Speed ◽  
Big Data Analytics ◽  
Huge Amount ◽  
Government Sector ◽  
Big Data Technologies ◽  
Survey Results

In the current day scenario, a huge amount of data is been generated from various heterogeneous sources like social networks, business apps, government sector, marketing, health care system, sensors, machine log data which is created at such a high speed and other sources. Big Data is chosen as one among the upcoming area of research by several industries. In this paper, the author presents wide collection of literature that has been reviewed and analyzed. This paper emphasizes on Big Data Technologies, Application & Challenges, a comparative study on architectures, methodologies, tools, and survey results proposed by various researchers are presented

scholarly journals The strategy for the development of labor activity of staff the formation of the organizational culture of the enterprise

2018 ◽  
Vol 11 (4) ◽  
pp. 327-337
Author(s):  
N. N. Saksina ◽  
S. A. Babenko
Keyword(s):  
Organizational Culture ◽  
Personnel Management ◽  
Psychological Climate ◽  
Effective Management ◽  
Management Decisions ◽  
Humanistic Approach ◽  
Positive Assessment ◽  
High Level ◽  
Relationship Of ◽  
Culture And Climate

The article is devoted to an urgent problem-the formation of the organizational culture of the enterprise, ensuring the achievement of a high level of labor activity of the staff. The author notes the importance and effectiveness of the application in the practice of personnel management of social and psychological management methods.The article presents the conceptual framework, the distinctive feature of which is the use of the established and justified relationship of organizational culture with the categories of «socio-psychological climate» and «labor activity» of personnel in the valuable environment of the enterprise in the framework of the humanistic approach to personnel management. The formation of organizational culture is based on the achievement of the required (normative) correlation of signs of labor activity of the enterprise personnel with the values of its subjects. The normative model of organizational culture allows to evaluate the value environment of the enterprise with a statement of the type of labor activity of the personnel, the allocation of culture and climate zones in it, as well as to prepare effective management decisions on their adjustment.To implement the author’s concept developed methodical providing of forming of organizational culture includes the set of classifiers of types of economic activity and values of constituent entities of the enterprise and a technique of an assessment of the value of the environment and of management decisions. The peculiarity of the development is their focus on the innovative type of labor activity of the staff as the most effective.Results of approbation of methodical providing at the industrial enterprise which have received a positive assessment of the management are given. The proposed measures will improve the socio-psychological climate and strengthen the organizational culture. 

scholarly journals DIGITAL MARKETING DEVELOPMENT IN RUSSIA: PROBLEMS AND PROSPECTS

2020 ◽  
Vol 8 (1) ◽  
pp. 111-115
Author(s):  
Natal'ya Diesperova ◽  
Elena Shevereva
Keyword(s):  
Big Data ◽  
National Economy ◽  
Digital Technologies ◽  
Cloud Services ◽  
Digital Marketing ◽  
Digital Products ◽  
Digital Platforms ◽  
Business Opportunities ◽  
Data Market ◽  
Big Data Technologies

In modern conditions, the competitiveness of companies and the national economy is determined by their ability to apply digital technologies, including Big Data technologies. They offer great opportunities for increasing efficiency of marketing and other activities of the company. An analysis of the level of development of the Russian Big Data market, Russian cloud services and digital platforms made it possible to conclude that despite the fact that Russia has the prerequisites for creating digital products of “high redistribution”, only the fragmented development of digital platforms will greatly complicate this process. The solution is seen in the substantial participation of the state in the creation of digital platforms since business opportunities, both financial and information, are insufficient.

Entrepreneurship and Big Data

2019 ◽  
pp. 196-233
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Search Engines ◽  
Public Organizations ◽  
Added Value ◽  
Big Data Technologies ◽  
Strategic Interest

The range of possibilities opened up by big data technologies offers companies in all sectors a remarkable opportunity for development and transformation. And if the majorities are convinced of its strategic interest, many are wondering about the implementation of such a project. Today, companies using big data are search engines like Google; social networks like Facebook, Twitter, or LinkedIn; e-commerce websites like eBay, Ali Baba, or Amazon, etc. But, it would be premature to conclude that big data is reserved for large companies only and that they alone can gain added value from its use. Indeed, as the motorist uses the highway without having built it, the commercial or public organizations, whatever their size and their field of interests, will be able to benefit from the use of big data.

scholarly journals TORNADO: Intermediate Results Orchestration Based Service-Oriented Data Curation Framework for Intelligent Video Big Data Analytics in the Cloud

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3581
Author(s):  
Aftab Alam ◽  
Young-Koo Lee
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Content Management ◽  
General Purpose ◽  
Video Analytics ◽  
Big Data Technologies ◽  
Service Oriented ◽  
Intermediate Results ◽  
High Level

In the recent past, the number of surveillance cameras placed in the public has increased significantly, and an enormous amount of visual data is produced at an alarming rate. Resultantly, there is a demand for a distributed system for video analytics. However, a majority of existing research on video analytics focuses on improving video content management and rely on a traditional client/server framework. In this paper, we develop a scalable and flexible framework called TORNADO on top of general-purpose big data technologies for intelligent video big data analytics in the cloud. The proposed framework acquires video streams from device-independent data-sources utilizing distributed streams and file management systems. High-level abstractions are provided to allow the researcher to develop and deploy video analytics algorithms and services in the cloud under the as-a-service paradigm. Furthermore, a unified IR Middleware has been proposed to orchestrate the intermediate results being generated during video big data analytics in the cloud. We report results demonstrating the performance of the proposed framework and the viability of its usage in terms of better scalability, less fault-tolerance, and better performance.

CRIMINOLOGICAL FEATURES OF CORRUPTION-RELATED CRIMES IN THE FUEL AND ENERGY COMPLEX

2020 ◽  
pp. 23-27
Author(s):  
Сергей Иванович Вележев ◽  
Антон Михайлович Седогин
Keyword(s):  
Legal Protection ◽  
Criminal Activity ◽  
Criminal Cases ◽  
Law Enforcement Agencies ◽  
Energy Complex ◽  
Significant Damage ◽  
Study Results ◽  
Wide Range ◽  
Illegal Activities ◽  
High Level

В представленной статье авторами рассматриваются вопросы уголовно-правовой охраны топливно-энергетического комплекса Российской Федерации от преступных проявлений, в том числе от коррупционной противоправной деятельности должностных лиц. Такие действия причиняют значительный ущерб нормальному функционированию предприятий топливно-энергетического комплекса. Авторами приводятся результаты исследования некоторых криминологических характеристик должностных лиц, совершивших преступления коррупционного характера. Дан анализ причин и условий, способствующих совершению вышеуказанных противоправных действий. Определена типовая модель преступника для данной категории преступлений и его характеристики: в первую очередь, это высокий уровень компетентности, специальное образование и т. д. Авторами отмечается высокий уровень латентной преступности в данной отрасли. Предложены некоторые пути профилактики данной категории правонарушений. Исследование проводилось на основе анализа конкретных уголовных дел, возбужденных следственными органами по результатам оперативно-розыскной деятельности правоохранительных органов. In the article the authors consider the issues of criminal and legal protection of the fuel and energy complex of the Russian Federation from criminal activity including corrupt illegal practices of officials. The authors cite the results of some criminological characteristics study of the fuel and energy complex staff committed corruption crimes. As a result of these illegal actions significant damage is caused to the normal functioning of the fuel and energy enterprises. Such officials` actions determine not only a wide range of other illegal activities, but also lead to public outcry and discredit the industry as a whole. The analysis of the reasons and conditions contributing to the above illegal actions commission is given. A typical model of a criminal for a given crime category and its characteristics are determined. First of all it is a high level competence, special education, etc. A high level of latent crime in this industry is shown. The study results are presented on the example of specific criminal cases initiated by the investigating authorities based on the results of the operation detection activities of law enforcement agencies. Some ways of preventing this category of offenses are proposed.

Procurement Analytics: Enabling Data Architectures in the Age of Big Data

2020 ◽  
Author(s):  
Michael Goul ◽  
T. S. Raghu ◽  
Ziru Li
Keyword(s):  
Big Data ◽  
Academic Research ◽  
Research Literature ◽  
Structured Interviews ◽  
Data Space ◽  
Prescriptive Analytics ◽  
Data Architecture ◽  
The Future ◽  
High Level ◽  
Area Data

As procurement organizations increasingly move from a cost-and-efficiency emphasis to a profit-and-growth emphasis, flexible data architecture will become an integral part of a procurement analytics strategy. It is therefore imperative for procurement leaders to understand and address digitization trends in supply chains and to develop strategies to create robust data architecture and analytics strategies for the future. This chapter assesses and examines the ways companies can organize their procurement data architectures in the big data space to mitigate current limitations and to lay foundations for the discovery of new insights. It sets out to understand and define the levels of maturity in procurement organizations as they pertain to the capture, curation, exploitation, and management of procurement data. The chapter then develops a framework for articulating the value proposition of moving between maturity levels and examines what the future entails for companies with mature data architectures. In addition to surveying the practitioner and academic research literature on procurement data analytics, the chapter presents detailed and structured interviews with over fifteen procurement experts from companies around the globe. The chapter finds several important and useful strategies that have helped procurement organizations design strategic roadmaps for the development of robust data architectures. It then further identifies four archetype procurement area data architecture contexts. In addition, this chapter details exemplary high-level mature data architecture for each archetype and examines the critical assumptions underlying each one. Data architectures built for the future need a design approach that supports both descriptive and real-time, prescriptive analytics.

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