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Item Open Access IMPROVING INDICATORS OF DIGITAL MARKETING USING ARTIFICIAL INTELLIGENCE(СДУ хабаршысы - 2020, 2020) Kaiyp K. ; Alimanova M.Abstract. In recent years, artificial intelligence (AI) has become a growing trend in various fields: medicine, education and the automotive industry. AI also reached a business, namely the marketing department of various businesses. The goal of the article is to research how deeply AI is used in digital marketing. The authors asked two research questions - which areas of AI are used in marketing and what are the positive effects of chat bots on a business. To answer these questions, the authors conducted a study of secondary data with examples of AI used for marketing purposes. An analysis of the collected examples shows that AI is widely implemented in the field of marketing, although applications are at the operational level. This may be the result of the careful implementation of the new technology, still at the level of experimentation with it. The uncertainty of the results of the implementation of AI can also affect caution when applying these innovations in practice. The collected examples proved that AI affects all aspects of the marketing structure, affecting both consumer value and the organization of marketing and business management. This document is important for the business, especially the idea of introducing artificial intelligence into marketing, developing innovation, and ideas on how to incorporate new skills into the marketing team needed for new technologyItem Open Access Statistical inference and machine learning in big data(Faculty of Engineering and Natural Science, 2019) Temirali A.In my practice. I met with different definitions: - Big Data is when data is more than 100GB (500GB. 1TB. who likes it) - Big Data is data that cannot be processed in Excel - Big Data is data that cannot be processed on a single computer. And even such: - Big Data is generally any data. - Big Data does not exist. marketers have invented it. Thus, under Big Data I will understand not some specific amount of data or even the data itself, but their processing methods. which allow distributed information to be processed. These methods cat? be applied both to huge data arrays (such as the content of all pages on the Internet) and to small ones (such as the content of this thesis).Item Open Access TEACHING BIG DATA ANALYTICAL PLATFORMS IN HIGHER EDUCATION FOR GRADUATE DEGREE STUDENTS(СДУ хабаршысы - 2018, 2018) Nurkey U.T. ; Bogdanchikov A.Abstract. An extensive archive of petabytes of data has been generated from modern information systems and digital technologies such as scientific data analysis, social data analysis, reference systems and Internet services journals. To investigate and extract knowledge from this enormous data much effort is needed. Due to this, Big Data Management Systems need to be integrated as part of the computing curriculum. In this article, we present examples of analysed tasks that can be processed as large data projects using Apache Hadoop, and it’s Map – Reduce, Apache Spark, Hive and Pig by demonstrating how each type of system can be integrated via sample datasets and data analysis tasks. The aim of this paper is to show how Big data analyzing tools can be educated through sample tasks, their solution and implementation.Item Open Access MapReduce Solutions Classification by Their Implementation(The International Journal of Engineering Pedagogy (iJEP), 2023) Orynbekova K.; Bogdanchikov A.; Cankurt S.; Adamov A.; Kadyrov Sh.Distributed Systems are widely used in industrial projects and scientific research. The Apache Hadoop environment, which works on the MapReduce paradigm, lost popularity because new, modern tools were developed. For example, Apache Spark is preferred in some cases since it uses RAM resources to hold intermediate calculations; therefore, it works faster and is easier to use. In order to take full advantage of it, users must think about the MapReduce concept. In this paper, a usual solution and MapReduce solution of ten problems were compared by their pseudocodes and categorized into five groups. According to these groups’ descriptions and pseudocodes, readers can get a concept of MapReduce without taking specific courses. This paper proposes a five-category classification methodology to help distributed-system users learn the MapReduce paradigm fast. The proposed methodology is illustrated with ten tasks. Furthermore, statistical analysis is carried out to test if the proposed classification methodology affects learner performance. The results of this study indicate that the proposed model outperforms the traditional approach with statistical significance, as evidenced by a p-value of less than 0.05. The policy implication is that educational institutions and organizations could adopt the proposed classification methodology to help learners and employees acquire the necessary knowledge and skills to use distributed systems effectively.Item Open Access USING ARTIFICIAL INTELLIGENCE TO IMPROVE DIGITAL MARKETING STRATEGIES(СДУ хабаршысы - 2020, 2020) Kaiyp K. ; Alimanova M.Abstract. The use of artificial intelligence (AI) will provide huge advantages in the digital marketing strategy of each company. This is a new face of productivity, efficiency and profitability. Making decisions about the start of a new era based on artificial intelligence should not replace the work of marketers or advertisers. It is here to unleash their true strategic and creative potential. For a business executives and marketers, the time has come to identify the problems facing the business or the marketing campaign, and how accurate ideas can solve these problems. This study discusses how AI could affect to effective of marketing strategies, shows real cases of using AI tools, and how companies could increase their profit.