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Andrey Prigulniy: The Use of Big Data in Business to Strengthen the Competitiveness of an Organization

Andrey Prigulniy says the purpose of this article is to study the impact of Big Data technology on the activities of businesses.

To implement the research goal, the following tasks were formulated: to assess the global and Russian Big Data market, as well as the leading market players; to consider the differences between Big Data analysis and traditional business intelligence; to study the experience of using Big Data technology in various sectors of the economy, as well as in the activities of organizations. A hypothesis was formulated about the impact of Big Data technology on improving the efficiency of entrepreneurship and increasing the competitiveness of businesses. The research methodology is based on the methods of comparative and systems analysis, firm economics, management theory. The analysis made it possible to obtain the following results: the differences between Big Data and conventional business intelligence have been identified; the techniques and methods of big data analysis that are used by organizations to solve managerial and production problems have been considered. The conditions for the successful implementation of Big Data projects in the activities of business organizations are proposed. It was revealed that companies that have implemented a high culture of working with Big Data achieve the greatest success.

Currently, digital technologies are changing the lives of people, organizations, and states. Companies and organizations are actively introducing mobile and cloud technologies, the Internet of Things, artificial intelligence systems, and others into business processes. Big Data provides new opportunities for development. Big Data technology accelerates innovation processes in the field of analytics in the public sector, science, and business organizations.

Practice shows that the use of Big Data for decision-making allows managers to radically rethink approaches to the development and implementation of an organization’s strategy. Companies are now showing great interest in Big Data. Many of them incorporate Big Data into

business models as a strategic resource.

Big Data is changing the way executives think about how organizations operate. Big Data provides information that provides new insights into business processes and enables more effective and better management decisions.

At the same time, it should be understood that the benefits of Big Data require new approaches to the analytical tools used in organizations, technologies, business processes and staff.

Experts from the McKinsey Institute define Big Data as datasets that are larger than

conventional databases and are complex in terms of storage, analysis and management.

In fact, Big Data technology involves the organization of work with huge amounts of information that comes from different sources (video, audio, geolocation, etc.) and has a high degree of renewal. Possible types of information sources that are used in companies to work on Big Data technology are presented in Table 1.

What is the difference between traditional business intelligence, which is used by companies

to solve management and operational problems, and Big Data analysis?

According to world renowned Japanese information and communications technology company Fujitsu [5], traditional business intelligence enables executives to solve problems based on evidence, while Big Data technologies enable them to solve predictive problems. Table 2 summarizes the differences between Big Data and business intelligence.

According to experts from Oracle [5], the Big Data technology differs from standard analytics,

when the results are obtained using standard mathematical / logical operations.

In the process of working with the database, they are sequentially cleaned in accordance with a certain model according to the following stages:

– putting forward a hypothesis;

– building an actual model and testing it for compliance with the hypothesis.

If the hypothesis is not confirmed, then the process is repeated again.

According to Research And Markets, at the end of 2019, the global market for Big Data analytics is $ 41.85 billion. In 8 years the market will grow to $ 155.13 billion. Growth will average

11.9 % per year.

The basis for the use of Big Data technology is cloud platforms that allow you to develop applications for working with Big Data.

Major companies use their own or hybrid clouds, small and medium-sized companies mainly use public clouds.

Small and medium-sized companies that do not have the resources and capabilities to independently implement Big Data projects use BBDaaS (Big Data as a service) technology, which is a cloud computing platform integrated with Big Data.

BBDaaS technology allows companies not only to save resources, but also to quickly solve analytical problems of Big Data in the cloud, giving all departments access to data at any time.

In January 2020, the European Union announced its intention to create a single Big Data market that will compete with the dominance of American and Chinese companies in the Big Data market.

According to experts from Frost & Sullivan, the global database market in 2021 will show an increase of 2.5 times compared to 2016 and will amount to 67.2 billion US dollars [6]. The average annual growth rate will be 35.9 %. Promising segments of the database market will be: manufacturing, financial sector, medicine, retail, environmental protection.

According to Research And Markets, the BDaaS market was $ 4.99 billion in 2018. The largest players in the BDaaS market are Amazon Web Services, Hewlett Packard Enterprise, IBM, Microsoft, Oracle, SAP, Teradata, Google, Accenture.

According to experts’ forecasts, the global BBDaaS market will grow to $ 61.42 billion by 2026. The average annual growth rate will be 36.9 %.

The analysis shows that the further growth of Big Data technologies will continue due to the following factors:

– the increasing accumulation of unstructured data arrays by companies;

– development of systems based on artificial intelligence (AI) and the Internet of things (IoT);

– growing demand for data mining and predictive analytics.

Currently, database technologies have already found wide application in the modern economy. Let’s consider some of the results of using the database in some sectors of the economy (Table 3).

Currently, a large number of analytical tools are used that are used for database analysis. These include: data mining, artificial neural networks, simulation, analytical data visualization, crowdsourcing, data fusion, cluster analysis, machine learning, predictive modeling and analytics, spatial analysis, etc.

The world’s leading IT companies are developing projects related to Big Data. Among them: Amazon, Dell, Facebook, Fujitsi, Google, IBM, HP, Linkedin, Microsoft, SAP, Yahoo, etc. Big Data is formed in the course of the functioning of these companies. By developing software for Big Data analysis, companies attract new customers and enter new market segments.

Analysis shows that Big Data is becoming part of the value chain of companies and increasing their competitiveness in the market.

As the experience of large companies – technology giants: Apple, Google, Facebook and others shows, they have achieved market success thanks to a strategic approach to data analysis and effective use of Big Data. Their strong competitive position is based on their ability to use Big Data in market strategy.

It is known that, in contrast to the traditions of Microsoft and IBM, in Apple technologies for the production of computers, operating systems and devices, developed in parallel and sequentially. It was a response to the next challenge of the digital age. Having reached the next limit in a separate direction, it was necessary to go further, using the accumulated arrays of data on demand, guided by consumer sentiment and having a new marketing strategy.

Apple has accumulated data over the years on how consumers are using Apple devices, how consumer tastes and preferences are changing, and changes in demand. This allowed the company to successfully adapt to changes, strengthen its competitive position in existing markets, and enter new markets. Thus, the emergence of the App Store, iTunes, as well as iPad and iPod devices allowed the company to take positions in the markets of music products, games, e-books and magazines, pushing out traditional players.

The analysis shows that with the introduction of digital technologies, consumer behavior in relation to companies is changing:

– increasing requirements for quality and service, provided goods/services;

– the need to access the product/service 24/7;

– variety and a large amount of available information about the product / service online;

– ensuring a high emotional level in interaction with companies.

Keeping in mind the increased demands of consumers has also prompted companies to use Big Data to create diverse models of interaction with them. At the same time, consumers are active elements of such models, leaving their feedback on companies, products/services in social networks, on company websites, participating in chats, forums, communities.

The analysis shows that a number of factors hinder the successful implementation of Big Data projects in the activities of business organizations. Let’s take a look at some of them:

– miscalculations in the development and organization of a Big Data project;

– the functionality of the project is not sufficiently developed;

– weak team of analysts;

– resistance to innovations from employees and management;

– lack of a culture of decision-making by managers based on Big Data analysis.

In addition, it is important that companies become more active in using industry-standard cloud-based database solutions from specialized vendors. In practice, many business organizations strive to create their own cloud infrastructure, which does not always work effectively.

The results of the analysis lead to the following conclusions:

– Big Data technologies are one of the key tools to improve the efficiency of organizations;

– the successful use of Big Data for decision-making helps to strengthen the market position of companies;

– the benefits of using Big Data are for companies that create and maintain a high culture of working with Big Data. This means that Big Data must be intelligently embedded in relevant business processes. Subdivisions should be formed, employees who are responsible for the completeness, timeliness and quality of the received Big Data should be determined.

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