Предизвикателства пред статистическата наука и бизнес анализаторската професия в ерата на големите данни и изкуствения интелект : Сборник с доклади от научна конференция
Challenges to the Statistical Science and the Business Analysis Profession in the Era of Big Data and Artificial Intelligence : Conference Proceedings
Contributor(s): Lina Kalaydzhieva (Editor)
Subject(s): Social Sciences, Economy, Business Economy / Management, Sociology, Social Informatics, Economic development, ICT Information and Communications Technologies, Socio-Economic Research
Published by: Университет за национално и световно стопанство (УНСС)
Keywords: statistical science; business analytics; big data; artificial intelligence
Summary/Abstract: The conference proceedings address the transformative challenges and opportunities faced by the statistical science and the business analytics in the modern era dominated by Big Data and Artificial Intelligence (AI). As data volumes and complexity grow, traditional analytical methods are integrated with AI technologies such as machine learning, deep learning, and natural language processing to uncover insights, improve decision-making, and optimize business processes across various domains. Key themes include the evolving synergy between business analysts and AI systems, the role of AI in strategic management especially in healthcare, the utilization of advanced Python libraries for big data modeling, and the adaptation of statistical methods to analyze unstructured data types like text, images, and audio. Empirical studies demonstrate AI’s impact on unemployment trend analysis, active aging research, market behavior, and project management within the context of digital transformation. The proceedings also explore behavioral attitudes toward AI adoption by future data analysts and lecturers, highlighting broad acceptance alongside concerns about algorithmic biases, job displacement, and ethical challenges. Practical case studies from Bulgarian enterprises emphasize turning analytical insights into actionable business decisions with leadership commitment, a data-driven culture, and interdisciplinary cooperation as pivotal success factors. Recommendations call for enhanced education in statistics and AI, improved data quality, transparent ethical standards, and adaptive frameworks for embedding AI responsibly within business and public sector analytics.
- Print-ISBN-13: 978-619-232-923-5
- Page Count: 177
- Publication Year: 2025
- Language: English, Bulgarian
Бизнес анализаторът и изкуственият интелект – сътрудници или съперници?
Бизнес анализаторът и изкуственият интелект – сътрудници или съперници?
(The Business Analyst and the Artificial Intelligence – Co-Workers or Rivals?)
- Author(s):Alexander Naydenov
- Language:Bulgarian
- Subject(s):Social Sciences, Economy, Business Economy / Management, Sociology, Social development, Social Informatics, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:5-12
- No. of Pages:8
- Keywords:business analyst; artificial intelligence; synergy
- Summary/Abstract:In the context of the rapidly evolving technologies and the increasing role of the artificial intelligence (AI) in business, this paper examines the coexistence and the potential for a fruitful partnership between the business analyst (BA) and the AI. The topic is placed in a current framework, highlighting the growing investments, the contribution of AI to productivity, and the growing interest from the business, the government, and the academia. Despite concerns about the displacement of BA by AI, the paper argues that the two sides can collaborate successfully, with AI taking on technical tasks while BA can focus on strategic and interpersonal issues.
Някои възможности за използване на големи данни при изследване на активното стареене
Някои възможности за използване на големи данни при изследване на активното стареене
(Exploring Specific Opportunities for Applying Big Data in Active Ageing Research – A Selective Perspective)
- Author(s):Ekaterina Tosheva
- Language:Bulgarian
- Subject(s):Social Sciences, Economy, Business Economy / Management, Sociology, Methodology and research technology, Social development, Social Informatics, Welfare services, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:13-20
- No. of Pages:8
- Keywords:active aging; big data; statistical research
- Summary/Abstract:Comprehensive research on active ageing necessitates access to reliable and upto- date statistical information. This report explores the potential of utilizing big data to examine various dimensions of the multidimensional concept of active ageing. It considers diverse sources of big data relevant to the study of this phenomenon and places particular emphasis on the specific challenges associated with its application in this context. The primary concern relates to limited access to digital technologies and disparities in digital literacy among older adults, which pose a significant risk of excluding specific subpopulations from statistical analyses based on big data. These challenges highlight the need for the development of new technologies and methodologies, ethical frameworks, and interdisciplinary collaboration, as well as effective strategies for their implementation in the study of active ageing.
Изследване на безработицата в България през периода от 2003 до 2024 г. Декомпозиране на динамичен ред с R и изкуствен интелект
Изследване на безработицата в България през периода от 2003 до 2024 г. Декомпозиране на динамичен ред с R и изкуствен интелект
(Unemployment Research in Bulgaria in the Period from 2003 to 2024. Decomposition of a Dynamic Series with R and Artificial Intelligence)
- Author(s):Iva Raycheva
- Language:Bulgarian
- Subject(s):Economy, Business Economy / Management, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:21-29
- No. of Pages:9
- Keywords:unemployment; trend; seasonal component; decomposition; artificial intelligence
- Summary/Abstract:Unemployment is one of the phenomena that arouses continuous interest and is directly related to the labor force and well-being among the society. Within the framework of the study of unemployment in Bulgaria during the period 2003 – 2024, periods of increase and decrease in the unemployment rate have been identified, some of which can be associated with the global financial and economic crisis in 2008. The main method used in this report is the decomposition of the dynamic series of unemployment. The method was performed using the specialized open source software R and the artificial intelligence ChatGPT.
Modeling Big Data Using Python
Modeling Big Data Using Python
(Modeling Big Data Using Python)
- Author(s):Vesela Dimitrova
- Language:English
- Subject(s):Social Sciences, Economy, Business Economy / Management, Sociology, Methodology and research technology, ICT Information and Communications Technologies
- Page Range:30-40
- No. of Pages:11
- Keywords:big data analysis; machine learning; Python libraries; econometric modeling by Python; Scikit-Learn; StatsModels
- Summary/Abstract:The numerous and ongoing improvements to Python libraries contribute to expanding the possibilities for processing and analyzing big data. The purpose of this paper is to explore the process of the big data analysis and provide an overview of various Python libraries that are suitable for statistical and econometric analysis: SciPy, Scikit-Learn and StatsModels. The paper also presents an example of a real-time data dependence model using Scikit-Learn and StatsModels.
Поведение и нагласи при използване на изкуствения интелект от бъдещи анализатори
Поведение и нагласи при използване на изкуствения интелект от бъдещи анализатори
(Behaviour and Attitudes towards the Use of the Artificial Intelligence by Future Analysts)
- Author(s):Ventsislava Stoyanova
- Language:Bulgarian
- Subject(s):Social Sciences, Economy, Business Economy / Management, Sociology, Methodology and research technology, Social development, Social Informatics, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:41-52
- No. of Pages:12
- Keywords:artificial intelligence; statistical methods; data processing data analysis
- Summary/Abstract:We have observed the rapid development of artificial intelligence (AI) and its increasingly widespread use in the human daily activities and work in recent years. This study analyzes the behaviour of future analysts in the artificial intelligence (AI) usе, as well as their attitudes towards its application in their future work involving data processing and analysis. The findings indicate that all participants use AI. Half of them use it on a daily basis. 96% use ChatGPT. According to the respondents, AI is expected to facilitate human tasks related to data processing and analysis but will not replace the necessity for expert involvement in this area.
The Impact of Artificial Intelligence on Lecturers in Bulgaria
The Impact of Artificial Intelligence on Lecturers in Bulgaria
(The Impact of Artificial Intelligence on Lecturers in Bulgaria)
- Author(s):James Osondu
- Language:English
- Subject(s):Social Sciences, Economy, Education, Business Economy / Management, Sociology, Higher Education , Social Informatics, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:53-68
- No. of Pages:16
- Keywords:artificial intelligence; lecturers
- Summary/Abstract:In the ever-evolving landscape of technology, artificial intelligence (AI) has emerged to challenge traditional paradigms and transform various sectors including higher education. It is now necessary to investigate how AI integration in higher education institutions in Bulgaria may affect instructional strategies, operational procedures, and student experiences. This article explores the implications of AI into Bulgaria higher education sector, highlighting the benefits, challenges, and future prospects. Moreover, it discusses the potential of AI to improve student experiences, streamline administrative tasks, and impacts on lecturers through transformed teaching and learning methods. It emphasizes the benefits of automated assessments, virtual classrooms, and personalised learning. Nevertheless, it is important to consider privacy and ethical concerns, as well as the future role of lecturers. Therefore, it recognises the necessity of precise regulations and policies to ensure the ethical and responsible application of AI in lecturing. By embracing AI while addressing its challenges, Bulgaria’s higher education institutions can deliver a more inclusive, efficient, and effective learning experience for all. In this way, recommendations are provided for stakeholders to navigate the transformative impact of AI on lecturers in Bulgaria.
Статистическите методи за анализ на неструктурирани данни като част от арсенала на изкуствения интелект
Статистическите методи за анализ на неструктурирани данни като част от арсенала на изкуствения интелект
(Statistical Methods for Analyzing Unstructured Data as Part of the Arsenal of Artificial Intelligence)
- Author(s):Bilyana Goleshova
- Language:Bulgarian
- Subject(s):Social Sciences, Economy, Business Economy / Management, Sociology, Methodology and research technology, ICT Information and Communications Technologies
- Page Range:69-80
- No. of Pages:12
- Keywords:unstructured data; artificial intelligence; statistical methods; processing and analysis
- Summary/Abstract:The constantly growing volume of unstructured data (in text, images, audio and video) affecting all spheres of socio-economic life in the modern world, combined with the advent of artificial intelligence and its increasingly frequent use, direct human thought to the question: What is the role of artificial intelligence (AI) in the processing and analysis of unstructured data? On the other hand, the mention of concepts such as „data“, „processing“ and „analysis“ directs us to statistical science and therefore to the role of statistical methods in the analysis of unstructured data. Therefore, this paper focuses on the mean statistical methods for analyzing unstructured data in the context of AI. It presents key statistical techniques used to process and interpret different types of unstructured data. Challenges and future directions in the use of statistical methods for analyzing unstructured data in AI are discussed. Finally, it was concluded that the importance of statistical methods for analyzing unstructured data as part of the AI arsenal is undeniable and that statistical methods are the foundation for developing reliable, accurate, and clear AI models. The other conclusion that was drawn is that ongoing research in the field of statistical methods and machine learning provides reliable future predictions for developments in the field.
Роля на проектното управление в условия на дигитална трансформация
Роля на проектното управление в условия на дигитална трансформация
(The Role of Project Management in the Context of Digital Transformation)
- Author(s):Svetla Tsenova
- Language:Bulgarian
- Subject(s):Social Sciences, Economy, Business Economy / Management, Sociology, Social Informatics, ICT Information and Communications Technologies
- Page Range:81-96
- No. of Pages:16
- Keywords:digital transformation; agile project management; disruption; success factors; strategic drift
- Summary/Abstract:The process of digital transformation (DT) has a significant impact on the way organizations operate and manage projects. This article aims to explore the role of project management in supporting and guiding digital transformation, drawing on both case studies from practice and current academic research from scholarly platforms such as Scopus, Elsevier, and ResearchGate. Both theoretical frameworks and practical aspects are analyzed to provide a comprehensive perspective on ensuring the smooth and effective implementation of digital transformation within organizations, with the goal of achieving optimal benefits for the economy, corporate social responsibility, and sustainable ecological development. In digital transformation processes of growing importance, science and practice strive to identify relevant success factors that can serve as leverage points for maximizing strategic advantages in modern organizational management. This follows the ancient saying attributed to Archimedes: „Give me a place to stand and a lever, and I will move the Earth“ (1) The success factors represent the fulcrum points, and (2) the skills of managers – the levers – which, through skillful project management and effective communication, transform traditional organizations into future-ready entities. This way, organizations are seen as being capable of overcoming the risks of strategic drift and harnessing disruptive change to their advantage.
От данни към действие: стратегии за превръщане на аналитични резултати в ефективни бизнес решения
От данни към действие: стратегии за превръщане на аналитични резултати в ефективни бизнес решения
(From Data to Action: Strategies for Turning Analytical Insights into Effective Business Decisions)
- Author(s):Ivan Mitkov
- Language:Bulgarian
- Subject(s):Economy, Business Economy / Management, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:97-106
- No. of Pages:10
- Keywords:business analytics; managerial decision-making; data-to-action; organizational transformation; SMES (small and medium-sized enterprises)
- Summary/Abstract:In a context of increasing digitalization, the ability of organizations to turn analytical insights into managerial action is a key strategic advantage. This paper examines critical enablers of this process through case studies of Vivacom and Telelink Business Services, applying the Gartner analytics maturity model. Key success factors identified include leadership commitment, data-driven culture, technological infrastructure, and interpretive skills. Practical recommendations are offered for both SMEs and large enterprises in Bulgaria, emphasizing the need for an interdisciplinary approach where data is the starting point – not the end – of a meaningful decision-making process.
Синергия между статистическата наука и бизнес анализа: адаптиране към ерата на големите данни и изкуствения интелект
Синергия между статистическата наука и бизнес анализа: адаптиране към ерата на големите данни и изкуствения интелект
(Synergy between Statistical Science and Business Analytics: Adapting to the Era of Big Data and Artificial Intelligence)
- Author(s):Stefan Fenerski
- Language:Bulgarian
- Subject(s):Social Sciences, Economy, Business Economy / Management, Sociology, Methodology and research technology, Social Informatics, ICT Information and Communications Technologies
- Page Range:107-116
- No. of Pages:10
- Keywords:synergy; business analytics; big data; artificial intelligence (AI); linear regression
- Summary/Abstract:This report explores the synergy between statistical science and business analysis, focusing on their adaptation to the era of Big Data and Artificial Intelligence (AI). As businesses face an increasing volume and complexity of data, statistical methods provide the essential tools for interpreting and analyzing data effectively. The report highlights the importance of techniques like linear regression, which is widely used for forecasting and analyzing trends in large datasets. It also examines how AI technologies, such as machine learning and deep learning, complement statistical methods by enabling automated analysis and more accurate predictions. Through practical examples, such as predicting sales based on advertising expenses, the report demonstrates the application of statistical methods in real-world business scenarios. Furthermore, the integration of AI enhances the value extracted from data, optimizing decision-making and improving operational efficiency. Despite the challenges of handling vast amounts of data, the report emphasizes the importance of combining statistical science with modern AI tools to achieve competitive advantages in today’s fast-paced business environment. The report concludes with recommendations for businesses to invest in training, improve data quality, and integrate AI with traditional statistical methods for better decision-making and long-term success.
Ролята на изкуствения интелект в стратегическото управление на здравните грижи
Ролята на изкуствения интелект в стратегическото управление на здравните грижи
(The Role of Artificial Intelligence in the Strategic Management of Healthcare Services)
- Author(s):Stanimira Tomova
- Language:Bulgarian
- Subject(s):Social Sciences, Economy, Business Economy / Management, Sociology, Management and complex organizations, Policy, planning, forecast and speculation, Social Informatics, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:117-130
- No. of Pages:14
- Keywords:rtificial intelligence; strategic management; healthcare services; forecasting, efficiency
- Summary/Abstract:This article explores the role of artificial intelligence (AI) in the strategic management of healthcare services, emphasizing its potential to transform systems into more efficient, sustainable, and patient-centered models. The research is based on a qualitative methodological approach, incorporating critical analysis of scientific literature, best practices from leading healthcare institutions, and international policies. It presents key AI tools that support managerial processes such as planning, forecasting, resource allocation, and performance evaluation. Best practices from hospitals such as Mount Sinai, Mayo Clinic, and Cleveland Clinic are analyzed, showcasing how AI is used for predictive analytics, optimization, and strategic decision-making. The main advantages of AI integration are outlined, including improved risk management, enhanced financial planning, and increased transparency. Additionally, challenges such as fragmented data, algorithmic bias, staff resistance, and infrastructure deficiencies are discussed. The article concludes by proposing a strategic approach based on collaboration, ethical regulation, and leadership to ensure the successful implementation of AI in healthcare services.
Статистическо изследване на борсовата търговия на "Софийска стокова борса" АД в контекста на изкуствения интелект
Статистическо изследване на борсовата търговия на "Софийска стокова борса" АД в контекста на изкуствения интелект
(Statistical Study of Commodity Trading on Sofia Commodity Exchange AD in the Context of Artificial Intelligence)
- Author(s):Toma Tomov
- Language:Bulgarian
- Subject(s):Economy, Business Economy / Management, Micro-Economics, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:131-143
- No. of Pages:13
- Keywords:gasoline; spot trading; energy products; energy commodity trade; commodity exchange
- Summary/Abstract:The report examines the dynamics of gasoline A95H, one of the main exchangetraded commodities on the Sofia Commodity Exchange AD. The study aims to identify patterns in trading to support exchange management and provide useful information to market participants (end clients, member firms, and brokers). The research is two-pronged, involving data analysis using IBM's statistical software SPSS and xAI's AI assistant Grok. The analyzed data is monthly and based on actual concluded transactions.
Анализ на проучването на пазара и изследването на потребителско поведение чрез обработка на големи данни
Анализ на проучването на пазара и изследването на потребителско поведение чрез обработка на големи данни
(Analysis of Market Research and Consumer Behavior Studies through Big Data Processing)
- Author(s):Svetla Stoynova
- Language:Bulgarian
- Subject(s):Economy, Business Economy / Management, Marketing / Advertising, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:144-153
- No. of Pages:10
- Keywords:big data; market research; consumer behavior; statistical analysis; digital technologies
- Summary/Abstract:This report examines modern approaches to market research and consumer behavior analysis by combining classical statistical methods with big data processing technologies. In the context of accelerated digitalization and the growing volume of information, it is necessary to develop integrated analytical solutions that merge the reliability of traditional statistics with the innovations of modern technology. The report presents key methods for collecting, processing, and interpreting market information, with a particular focus on the role of established statistical approaches enhanced by digital tools for automated data processing and real-time visualization. It discusses the challenges faced by statistical science regarding data quality in the digital environment. In this regard, the RMS methodology developed by the company NIQ is presented as a good example of an integrated approach. Its main stages are described, including the definition of the general population, data collection through electronic and manual audits, classification of product information, and the use of software tools for analysis and visualization. In conclusion, the report emphasizes both the benefits of technological advancement and the necessity to preserve and further develop statistical principles, which remain fundamental to reliable and applicable analysis in the digital age.
Статистическо изследване на влиянието на медиите върху ценностната система на гражданите на България, Австрия, Германия, Финландия, Гърция и Португалия
Статистическо изследване на влиянието на медиите върху ценностната система на гражданите на България, Австрия, Германия, Финландия, Гърция и Португалия
(Statistical Analysis of the Influence of Media on the Value System of Citizens in Bulgaria, Austria, Germany, Finland, Greece, and Portugal)
- Author(s):Ivana Vodenicharova
- Language:Bulgarian
- Subject(s):Social Sciences, Economy, Media studies, Business Economy / Management, Communication studies, Sociology, Evaluation research, Sociology of Culture, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:154-159
- No. of Pages:6
- Keywords:values; media; society; internet; statistics
- Summary/Abstract:This study examines the influence of the media environment on the value system of citizens in six European countries: Bulgaria, Austria, Germany, Finland, Greece, and Portugal. The main objective is to determine the extent to which media contribute to the formation and prioritization of personal values. A quantitative methodological approach is applied, including univariate frequency distributions and hypothesis testing. The study targets individuals aged 15 and above, focusing on the factor-driven nature of value preferences. The research utilizes Shalom Schwartz’s typology, which includes ten basic human values. The data reveal significant intercultural differences – for instance, „power“ emerges as a dominant value in Austria, Bulgaria, Germany, and Finland, while „stimulation“ prevails in Greece and Portugal. Results also indicate that daily internet use correlates with specific value orientations. The study highlights the importance of fostering media literacy and critical thinking as essential tools for sustainably mitigating the influence of media on both individual and collective value systems.
Сравнителен анализ на статистически и AI базирани модели при оценка на влиянието на новини върху пазарната цена на Bitcoin
Сравнителен анализ на статистически и AI базирани модели при оценка на влиянието на новини върху пазарната цена на Bitcoin
(Comparative Analysis of Statistical and AI-Based Models in Assessing the Impact of News on the Market Price of Bitcoin)
- Author(s):Nikita Shvetsov
- Language:Bulgarian
- Subject(s):Social Sciences, Economy, Sociology, Policy, planning, forecast and speculation, Social Informatics, Financial Markets, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:160-172
- No. of Pages:13
- Keywords:news impact; sentiment analysis; machine learning; price movement forecasting; ai-based models
- Summary/Abstract:This study examines the impact of news sentiment and Google Trends indices on the price of Bitcoin by applying both classical and modern statistical models. Various methods are employed for the analysis, including linear regression, XGBoost, and LSTM. The model is based on temporal dependencies between the sentiment index, trend interest, and market movement. The results indicate that the regression model with the variables NSI and Trend partially explains price movements, with NSI showing a positive effect. XGBoost demonstrates high predictive accuracy (R² ≈ 0.78), while LSTM captures nonlinear and deep dependencies in the data. The analysis reveals that the effect of news is highly short-term, making classical ARIMA models less applicable. The study contributes to a better understanding of behavioral factors and highlights the role of AI models in economic forecasting.
Проблеми и предизвикателства пред науката статистика, свързани с анализа на данни чрез навлизането на изкуствения интелект
Проблеми и предизвикателства пред науката статистика, свързани с анализа на данни чрез навлизането на изкуствения интелект
(Problems and Challenges for the Science of Statistics, Related to Data Analysis, through the Advent of Artificial Intelligence)
- Author(s):Petya Videnova
- Language:Bulgarian
- Subject(s):Social Sciences, Economy, Business Economy / Management, Sociology, Methodology and research technology, Social Informatics, ICT Information and Communications Technologies, Socio-Economic Research
- Page Range:173-176
- No. of Pages:4
- Keywords:advantages; disadvantages; artificial intelligence; problems; statistics
- Summary/Abstract:This report aims to examine the problems posed to the science of statistics by the rapid advent of artificial intelligence. The advantages and disadvantages of artificial intelligence will be reviewed, in terms of how useful it is as a means of solving problems of all kinds.
