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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">kaz44</journal-id><journal-title-group><journal-title xml:lang="ru">Вестник Университета Шакарима. Серия технические науки</journal-title><trans-title-group xml:lang="en"><trans-title>Bulletin of Shakarim University. Technical Sciences</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2788-7995</issn><issn pub-type="epub">3006-0524</issn><publisher><publisher-name>«Шәкәрім университеті» КеАҚ</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.53360/2788-7995-2023-4(12)-4</article-id><article-id custom-type="elpub" pub-id-type="custom">kaz44-507</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>АВТОМАТИЗАЦИЯ И ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ (ОРИГИНАЛЬНАЯ СТАТЬЯ)</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>AUTOMATION AND INFORMATION TECHNOLOGY (ORIGINAL ARTICLE)</subject></subj-group></article-categories><title-group><article-title>Роль искусственного интеллекта и обучения macnine в бизнес-аналитике</article-title><trans-title-group xml:lang="en"><trans-title>The role of artificial intelligence and macnine learning in business intelligence</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0009-4109-1387</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Абалканов</surname><given-names>М. М.</given-names></name><name name-style="western" xml:lang="en"><surname>Abalkanov</surname><given-names>M. M.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Мирас Маратович Абалканов – магистрант</p><p>010000,  г. Астана, проспект Мангилик Ел, 55/11</p></bio><bio xml:lang="en"><p>Miras Maratovich Abalkanov – master's degree</p><p>010000, Astana, Mangilik El avenue, 55/11</p></bio><email xlink:type="simple">abalkanovmiras@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-3830-6905</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Абитова</surname><given-names>Г. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Abitova</surname><given-names>G. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Гульнара Аскеровна Абитова – PhD, доцент</p><p>010000, г. Астана, проспект Мангилик Ел, 55/11</p></bio><bio xml:lang="en"><p>Gulnara Askerovna Abitova – PhD, Associate Professor</p><p>010000, Astana, Mangilik El avenue, 55/11</p></bio><email xlink:type="simple">gulya.abitova@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">Astana IT University<country>Казахстан</country></aff><aff xml:lang="en">Astana IT University<country>Kazakhstan</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>28</day><month>12</month><year>2023</year></pub-date><volume>1</volume><issue>4(12)</issue><fpage>25</fpage><lpage>30</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Абалканов М.М., Абитова Г.А., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Абалканов М.М., Абитова Г.А.</copyright-holder><copyright-holder xml:lang="en">Abalkanov M.M., Abitova G.A.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://tech.vestnik.shakarim.kz/jour/article/view/507">https://tech.vestnik.shakarim.kz/jour/article/view/507</self-uri><abstract><p>В этой статье исследуется, как искусственный интеллект (ИИ) и машинное обучение (ML) меняют способы использования данных предприятиями. В мире, где данные очень важны, многие компании используют искусственный интеллект и ML, чтобы максимально эффективно использовать свои данные. В этом исследовании рассматривается, как искусственный интеллект и ML используются в бизнес-аналитике (BI), которая заключается в сборе и анализе данных, помогающих компаниям принимать разумные решения. Сначала мы рассмотрим старый способ работы с BI и то, как он не мог справиться с огромным объемом данных, которыми мы располагаем сегодня. Затем мы видим, как искусственный интеллект и ML используются для решения этой проблемы. Эти технологии помогают автоматически обрабатывать данные, прогнозировать будущие тенденции и находить важную информацию в больших массивах данных. Мы также ознакомимся с некоторыми реальными примерами из разных отраслей, чтобы увидеть, как искусственный интеллект и ML помогают компаниям принимать более эффективные решения. Эти примеры показывают, как компании могут получать более точные данные, быстрее принимать решения и лучше прогнозировать ситуацию, используя искусственный интеллект и ML в своей BI. Мы также говорим о некоторых проблемах и вещах, о которых нам нужно подумать при использовании искусственного интеллекта и ML в BI, например, о том, чтобы убедиться, что мы используем эти технологии ответственно и справедливо. Подводя итог, это исследование показывает, что искусственный интеллект и ML – это не просто инструменты, они меняют то, как мы работаем с BI. Используя эти технологии, компании могут лучше анализировать свои данные, оставаться конкурентоспособными и вывести свою бизнес-аналитику на новый уровень. </p></abstract><trans-abstract xml:lang="en"><p>This article explores how Artificial Intelligence (AI) and Machine Learning (ML) are changing the way businesses use data. In a world where data is super important, many companies are using AI and ML to make the most of their data. This study looks at how AI and ML are being used in Business Intelligence (BI), which is all about collecting and analyzing data to help businesses make smart decisions. First, we look at the old way of doing BI and how it couldn't handle the huge amount of data we have today. Then, we see how AI and ML are being used to solve this problem. These technologies help by automatically processing data, predicting future trends, and finding important information in big piles of data. We also check out some real-life examples from different industries to see how AI and ML are helping companies make better decisions. These examples show how businesses can get more accurate data, make decisions faster, and predict things better by using AI and ML in their BI. We also talk about some challenges and things we need to think about when using AI and ML in BI, like making sure we use these technologies in a responsible and fair way. In summary, this research shows that AI and ML are not just tools, but they're changing the way we do BI. By using these technologies, companies can get better insights from their data, stay competitive, and take their BI to the next level. </p></trans-abstract><kwd-group xml:lang="ru"><kwd>Информационные технологии</kwd><kwd>Машинное обучение</kwd><kwd>Искусственный интеллект</kwd><kwd>Бизнес-аналитика</kwd><kwd>Технологии и аналитика аналитики</kwd><kwd>Интеллектуальные решения</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Information technology</kwd><kwd>Machine Learning</kwd><kwd>Artificial Intelligence</kwd><kwd>Business Intelligence</kwd><kwd>Tech &amp; Analytics</kwd><kwd>Smart Decisions</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Gandomi, A., &amp; Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. 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