THE IMPACT OF BIG DATA ON SMALL BUSINESS MARKET RESEARCH

ВЛИЯНИЕ БОЛЬШИХ ДАННЫХ НА ПРОВЕДЕНИЕ ИССЛЕДОВАНИЙ РЫНКА МАЛОГО БИЗНЕСА

Одо Бонавентура Эвезуга

студент, муниципальная средняя школа, штат Энугу

Федеративная Республика Нигерия, г. Ибенда-Удену

Эджиофор Джонсон Чидибере

студент, Факультет сестринского дела, Российский университет дружбы народов имени Патриса Лумумбы,

РФ, г. Москва

ABSTRACT

This review article examines the evolution of big data and examines its characteristics to identify big data features that are relevant to small business problems. An attempt is also made to dispel the myth that the use of big data technology is only suitable for large businesses by providing real successful examples of the use of big data by small businesses in different countries. The work consists of an introduction, main part and conclusion, and a list of references.

АННОТАЦИЯ

В данной обзорной статье рассматривается эволюция больших данных, в статье изучаются характеристики больших данных с целью выявления функций больших данных, актуальных для бизнес-задач малого бизнеса. Так же предпринимается попытка развеять миф о пригодности использования технологии больших данных лишь для крупного бизнеса путем приведения реальных успешных примеров использования больших данных малым бизнесом в разных странах. Работа состоит из введения, основной части и заключения, списка литературы.

Keywords: big data, small business, data array, marketing, risks.

Ключевые слова: большие данные, малый бизнес, массив данных, маркетинг, риски.

Introduction

Today, in the age of technology and the Internet, data volumes are growing exponentially. And since digitalization has reached all spheres of human life, the small business management system also needs to be modernized [4]. The main priorities of business in general are: increasing the company's profits and its competitiveness by increasing customer loyalty. This can be achieved through an individual approach to customers and constant collection of feedback from them. And with the growth of the market and target audience, it becomes almost impossible to process huge amounts of information manually. In this case, modern IT comes to the rescue, which allows you to expand the range of analytical capabilities of the marketing departments of companies of any size. Thus, this article examines the nature of big data, its evolution as evidence of the successful applicability of this tool in small business.

The object of this study is big data as a marketing tool for small businesses. The subject of the study is the possibilities and advantages of using big data in small businesses.

The aim of the study is to determine the level of possibility of applying big data technologies in small businesses for the purpose of its development and optimization.

To achieve the stated goal, the following research objectives have been formulated:

1. To study the nature of big data technology and its evolution;

2. To analyze the level of technological capabilities of big data at the present stage;

3. To find out the possibility of using big data in small businesses in accordance with the challenges of small businesses;

4. To offer services based on big data that can optimize the work of small businesses.

Big data earlier and at the present stage of technological development

Big data is structured or unstructured data arrays that arrive at a higher speed and in ever-increasing volumes. This type of data requires special programs and hardware to store and process big data [8].

Big data is assessed through three main characteristics:

First, the volume of data - this factor determines the amount of data that a server can technically accommodate. Unstructured data can often have low density, which makes it difficult to immediately determine the value of this data and requires additional processing. This can be web page traffic data, social media channels, unstructured network traffic, etc. [1].

Secondly, data diversity as a characteristic implies that data belongs to different types. If we talk about the traditional data type, then this is a structured data type that is automatically saved in a relational database. However, a characteristic of big data is the semi-structured or unstructured nature of data. These include video, audio, text format data that require additional processing.

And finally, speed, the criterion that determines the number of units of information processed by servers per unit of time. Today, there are smart systems that can support data reception in near-real or real-time mode.

The big data systems themselves, as well as, the Hadoop system, appeared only at the beginning of this twenty years. The emergence of big data systems is directly related to the development of such current IT projects as Google*, iTunes, YouTube, The Facebook**, Twitter, Steam, Oblivion, and many others. During the development of Google*, the creators were puzzled by two pressing questions:

How to achieve the placement of terabyte-sized data arrays on different server devices without losing information and with constant access to it?

How to distribute the calculation of information to obtain a minimum percentage of failures in processing operations and with the greatest efficiency? [3, p. 110]

In 2003, the work “The Google File System*” was published, which allowed to solve the first question mentioned above. Figure 1 explains the new arrangement of servers and other elements, according to GFS [10].

Fig. 1. The new arrangement of servers and other elements, according to GFS

The main disadvantage of the first generations of big data was the impossibility of storing unstructured data due to limited volumes, but modern big data technologies do not have these limitations and are capable of storing terabytes of data [2, p. 13]. So, if before the beginning of 2006, huge arrays of unstructured data that companies had were practically useless, then after a breakthrough in big data technologies and the advent of AI, a wide range of opportunities opened for companies in the areas of CRM, Email marketing reports, social media analytics, publicly available data, Data lakes and much more [5, p. 91]. By analyzing hidden patterns of information, it helps companies extract the necessary information useful for its development [9].

Speaking in more detail about the services that are developed on the basis of big data technology, one cannot fail to mention SAS Viya. This software package was developed by SAS Institute Inc. This software works with sources such as the Internet, social networks, and freely available marketing analytics. Its advantage is that the software is capable of not only extracting data from all the listed sources, but also modifying, analyzing, and managing them [12]. Watson Analytics is presented as an analytical product of IBM Watson. The operating principle of this software is similar to SAS Viya, but its advantage is that this software is suitable for small business owners who do not have experience working with big data. A simple interface and high processing speed allow you to implement the software in business processes at any stage of business development and get advanced business analytics. The software allows you to integrate several components of business departments at once, such as HR, finance, sales, marketing and others [7]. The program identifies patterns and potential risks / weaknesses. Also, do not forget about classic software in the form of Google Analytics*, Zendesk and QuickBooks.

Risks and concerns in connection with big data usage for small business

Despite the huge number of advantages, their use in small businesses carries a number of risks that should be accepted or minimized. The first of these is Privacy and Security concerns. Collecting big data increases the risk of information leakage and unauthorized third-party interventions, resulting in the loss of data, and therefore customer trust [6].

The second serious risk is large expenses not only for the purchase of software, but also for the placement of servers for storing and processing information. Small businesses must have a good financial position in order to afford the processing of big data [11].

An equally important risk is the possible formation or reinforcement of existing racial, gender and other prejudices when collecting data. Moreover, collecting data with built-in prejudices entails new prejudices.

Conclusion

To conclude big data has become an integral part of not only technological but also economic progress in the modern world. As they improve, they significantly simplify business management not only for large giant companies, but also allow small businesses to optimize their processes in marketing, CRM, HR, finance, risk forecasting, etc. Despite the variety of big data software on the market and the multifunctionality of modern big data in small businesses, there are risks that must be considered when deciding to use big data by small businesses. These include the need to take additional measures to ensure data security and confidentiality. Companies must also be prepared to financially switch to big data software. The ethical issue of compliance with data collection measures also takes place.

*(По требованию Роскомнадзора информируем, что иностранное лицо, владеющее информационными ресурсами Google является нарушителем законодательства Российской Федерации – прим. ред.)

**Деятельность социальных сетей Instagram и Facebook, принадлежащих компании Meta Platforms Inc., признана экстремистской и запрещена на территории Российской Федерации

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