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Artykuły w czasopismach na temat „Operational Analytics Business Excellence”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Priyanka, Singh*1 Rajesh Kumar Upadhyay2 &. Dr. Monika Srivastava3. "THE ROLE OF HR ANALYTICS IN HIGHER EDUCATION INSTITUTION." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 7 (2017): 92–100. https://doi.org/10.5281/zenodo.823015.

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The HR analytics has emerged as a new fad for the management leaders that captured the head line for business world news. This paper tries to figure out the theoretical and conceptual the framework of analytics in higher education intuitions. The objectives of the study are to understand the role of HR analytics for education institution in increasing the organizational effectiveness and efficiency. The research used exploratory research design. Further study came up with categorizing the data analytics of industry it into Academic Analytics, Operational Analytics and special reference is give

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Eka Novalia Pusparini and Agussalim Agussalim. "Literature Review: Data Management, Data Analytics, and Business Intelligence for Organization." Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi 2, no. 4 (2024): 133–42. http://dx.doi.org/10.61132/neptunus.v1i4.429.

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This study was conducted to examine the functions of data management, data analytics, and business intelligence across various organizational sectors. A literature review was performed to gain a broader understanding of the topic, utilizing research backgrounds from different countries, with ten studies selected for review from multiple sources. The results indicate that efficient data management, combined with robust analytical capabilities and business intelligence tools, is crucial for modern organizations seeking to achieve operational excellence and strategic growth. By implementing the a

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Likhit Verma. "Future trends of lean six sigma and process excellence in business operations." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 4233–43. https://doi.org/10.30574/wjarr.2025.26.2.2088.

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The evolution of Lean Six Sigma in the digital era represents a transformative shift in operational excellence paradigms across industries. This transition from traditional improvement methodologies to technology-enhanced frameworks has fundamentally altered how organizations identify inefficiencies, implement solutions, and sustain performance gains. The integration of artificial intelligence, hyperautomation, digital twins, and other emerging technologies with established Lean Six Sigma principles creates synergistic capabilities that transcend conventional process excellence limitations. Or

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Lohinova, Olha. "BUSINESS ANALYTICS AS A KEY COMPONENT OF THE DIGITAL TRANSFORMATION OF COMPANIES." Economies' Horizons, no. 2(31) (May 19, 2025): 83–91. https://doi.org/10.31499/2616-5236.2(31).2025.330124.

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This article explores the role of business analytics as a crucial component in the digital transformation of modern companies. It examines contemporary trends in the use of analytical tools to enhance decision-making, streamline business processes, and improve organizational competitiveness. The research highlights the strategic importance of business analytics in fostering data-driven decision-making and promoting sustainable growth in a digital economy. Various types of analytics-descriptive, diagnostic, predictive, and prescriptive-are discussed in the context of their application across ma

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Rodrigues, Nilima James. "Predictive Analytics and Artificial Intelligence: Advancing Business Analytics in the Medical Devices Industry." European Journal of Computer Science and Information Technology 13, no. 41 (2025): 75–90. https://doi.org/10.37745/ejcsit.2013/vol13n417590.

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Predictive analytics and artificial intelligence are transforming business processes across the medical device industry, enabling more sophisticated decision-making and operational excellence. This content explores key applications of these technologies across financial planning, demand forecasting, customer analytics, and supply chain management domains. The integration of advanced algorithms with domain-specific data streams allows medical device manufacturers to anticipate market shifts, optimize inventory positions, personalize customer engagement, and build resilient supply networks. Whil

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Govindaraja Babu Komarina and John Wesly Sajja. "The Transformative Role of SAP Business Technology Platform in Enterprise Data and Analytics: A Strategic Analysis." Journal of Computer Science and Technology Studies 7, no. 5 (2025): 228–35. https://doi.org/10.32996/jcsts.2025.7.5.29.

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This article examines the transformative role of SAP Business Technology Platform (BTP) in revolutionizing enterprise data management and analytics capabilities. Through comprehensive analysis of implementation results across multiple organizations, the article demonstrates how BTP serves as a crucial integration layer that connects disparate data sources while enabling advanced analytics and artificial intelligence capabilities. The article explores four key aspects: BTP's unified data platform architecture, its integration capabilities and data management excellence, advanced analytics and i

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Parmar, Ahaan. "AI-DRIVEN DATA ANALYTICS FOR REAL-TIME DECISION-MAKING." IINTERNATIONAL JOURNAL OF PROGRESSIVE RESEARCH IN ENGINEERING MANAGEMENT AND SCIENCE 5, no. 5 (2025): 372–86. https://doi.org/10.58257/IJPREMS40153.

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Artificial intelligence-powered data analytics functions as an indispensable transformational force that helps organizations obtain immediately useful information from large databases while responding rapidly to shifting market conditions across different business sectors. This research analyzes how artificial intelligence, when connected to data analytics, drives transformational development through analyses of real-time applications along with advantages and obstacles that exist in addition to future analytical patterns. Through their union, data analytics and artificial intelligence systems

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Zulkarnain, Andy, Ramzi Zainum Ikhsan, Nanda Septiani, and Victorianda. "Advancing Management Strategies with AI and IoT for Operational Excellence and Competitive Edge." APTISI Transactions on Management (ATM) 9, no. 1 (2025): 50–59. https://doi.org/10.33050/atm.v9i1.2396.

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As organizations face increasing competition and technological advancements, optimizing operations and managing resources efficiently is crucial for maintaining a competitive edge. The integration of emerging technologies like Artificial Intelligence (AI) and the Internet of Things (IoT) enhances efficiency, improves resource allocation, and drives growth. This study explores how AI and IoT adoption optimizes business processes, improves decision-making, and fosters a competitive advantage Using a quantitative approach, data from 200 executives in AI and IoT-implemented industries were analyze

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DANG QUOC, Huu. "Appling Power BI for improved retail business analytics and decision-making." Applied Computer Science 21, no. 2 (2025): 154–63. https://doi.org/10.35784/acs_7130.

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In the rapidly evolving retail industry, data-driven decision making is critical to maintaining competitive advantage and operational efficiency. This paper explores the diverse applications of Microsoft Power BI (MPBI) in retail, highlighting its impact on real-time data management, sales analysis, inventory optimization, customer insights, and supply chain performance. By synthesizing findings from recent studies and presenting empirical data from case studies, we demonstrate how Power BI's advanced analytics and visualization capabilities can transform raw data into actionable insights. Our

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Nyangoma, Daphine, Ejuma Martha Adaga, Ngodoo Joy Sam-Bulya, and Godwin Ozoemenam Achumie. "Operational Excellence in SMEs: A Conceptual Framework for Optimizing Logistics and Service Delivery Systems." Journal of Frontiers in Multidisciplinary Research 5, no. 1 (2024): 149–56. https://doi.org/10.54660/.ijfmr.2024.5.1.149-156.

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This paper explores the concept of operational excellence in Small and Medium-sized Enterprises (SMEs), focusing on optimizing logistics and service delivery systems. Operational excellence is crucial for SMEs to enhance efficiency, reduce costs, and improve customer satisfaction, which are all essential for their survival and growth in competitive markets. The study examines key frameworks like Lean Management, Six Sigma, and Total Quality Management (TQM), illustrating how they can be applied to streamline operations and improve service quality. The paper also emphasizes the role of key perf

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Feng, ZuYing, and ZhiYing Zhang. "IoT in Retail: Transforming Big Data Analytics for Business Success." International Journal of Engineering and Science Invention 13, no. 9 (2024): 69–75. http://dx.doi.org/10.35629/6734-13096975.

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The fusion of Internet of Things (IoT) technology in the retail sector marks the dawn of a transformative era in data-driven decision-making. This study sets out to investigate how retailers can strategically integrate IoT solutions to amplify their big data analytics capabilities, thereby enha ncing business acumen. By delving into IoT's pivotal role, this work emphasizes its capacity to gather real-time insights from a network of interconnected devices and systems, empowering retailers to make operationally optimized, customer-centric decisions that unlock fresh revenue opportunities.Core to

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Varun Narayan Bhat. "Enterprise Digital Transformation: Leveraging AI/ML and Automation for Operational Excellence." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 3537–45. https://doi.org/10.32628/cseit251112373.

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This comprehensive article examines the transformative impact of Artificial Intelligence (AI), Machine Learning (ML), and automation technologies on enterprise digital transformation within the technology sector. It explores how leading organizations leverage predictive analytics, intelligent automation, and real-time decision-making capabilities to optimize their operations and enhance customer experiences. Through detailed case studies and industry analysis, it demonstrates the significant benefits of AI/ML integration across software development, IT service management, and cloud operations.

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Soliman, Karim, Afroze Nazneen, Adina Ambreen, Rasheedul Haque, and Vikramjeet Jeet. "Business analytics as a driver of organizational performance: Evidence from the pharmaceutical industry." International Journal of Innovative Research and Scientific Studies 8, no. 2 (2025): 3857–71. https://doi.org/10.53894/ijirss.v8i2.6114.

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This study investigates the role of business analytics in enhancing organizational performance within the pharmaceutical industry. Business analytics, encompassing data collection, analytical tools, technology, human resources, strategic alignment, performance measurement, and compliance, is crucial for driving informed decision-making and strategic planning. A quantitative approach was employed, surveying 162 professionals across various managerial levels in pharmaceutical companies. A structured questionnaire assessed the impact of business analytics on organizational performance, focusing o

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Md Abdullah Al Mahmud, Nur Vanu, Sadia Islam Nilima, and Rakibul Hasan. "Enhancing Customer Experience and Business Operations in E-Commerce Platforms through Big Data Analytics." Journal of Business and Management Studies 3, no. 2 (2021): 288–95. https://doi.org/10.32996/jbms.2021.3.2.30.

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Big data analytics has revolutionized the e-commerce industry by enhancing customer experience and optimizing business operations. This thesis explores the multifaceted impact of big data analytics on e-commerce platforms, highlighting how personalized customer interactions and streamlined operations contribute to a competitive advantage. Through the integration of case studies and empirical data, the research delves into the ways e-commerce businesses can harness big data to understand customer preferences, predict purchasing behavior, and tailor marketing efforts. Additionally, the study exa

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Rahman, Md Musfiqur. "DATA ANALYTICS FOR STRATEGIC BUSINESS DEVELOPMENT: A SYSTEMATIC REVIEW ANALYZING ITS ROLE IN INFORMING DECISIONS, OPTIMIZING PROCESSES, AND DRIVING GROWTH." Journal of Sustainable Development and Policy 01, no. 01 (2025): 285–314. https://doi.org/10.63125/he1tfg25.

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This meta-analysis offers a comprehensive synthesis of empirical evidence on the strategic role of data analytics in business development, with particular emphasis on its contributions to informed decision-making, operational process optimization, financial planning, risk mitigation, and customer-centric growth. Drawing from a dataset of 112 peer-reviewed empirical studies published between 2010 and 2024, the study employs a meta-analytic methodology following PRISMA guidelines to ensure methodological rigor and analytical depth. The research systematically categorizes analytics into descripti

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Oluwaseun Badmus, Shahab Anas Rajput, John Babatope Arogundade, and Mosope Williams. "AI-driven business analytics and decision making." World Journal of Advanced Research and Reviews 24, no. 1 (2024): 616–33. http://dx.doi.org/10.30574/wjarr.2024.24.1.3093.

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The rapid advancement of Artificial Intelligence (AI) and Machine Language (ML) has revolutionized business analytics, transforming the way organizations make decisions. This paper explores the integration of AI-driven technologies into business analytics to enhance decision-making across various industries. By leveraging predictive and prescriptive analytics, AI enables organizations to not only analyse historical data but also forecast future trends, allowing for more informed, proactive strategies. Machine learning plays a pivotal role in automating data-driven decisions, offering real-time

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Oluwaseun, Badmus, Anas Rajput Shahab, Babatope Arogundade John, and Williams Mosope. "AI-driven business analytics and decision making." World Journal of Advanced Research and Reviews 24, no. 1 (2024): 616–33. https://doi.org/10.5281/zenodo.15010634.

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The rapid advancement of Artificial Intelligence (AI) and Machine Language (ML) has revolutionized business analytics, transforming the way organizations make decisions. This paper explores the integration of AI-driven technologies into business analytics to enhance decision-making across various industries. By leveraging predictive and prescriptive analytics, AI enables organizations to not only analyse historical data but also forecast future trends, allowing for more informed, proactive strategies. Machine learning plays a pivotal role in automating data-driven decisions, offering real-time

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Jayakrishnan, Mailasan, Abdul Karim Mohamad, and Mokhtar Mohd Yusof. "Developing railway supplier selection excellence using business intelligence knowledge management framework." International Review of Applied Sciences and Engineering 12, no. 3 (2021): 257–68. http://dx.doi.org/10.1556/1848.2021.00267.

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AbstractIn a broad scope, the term Information System (IS) is a scientific field of research study that approaches the scope of managerial, strategic, and operational activities complex in the storing, processing, distributing, gathering, and utilizing of knowledge and its associated technologies in organizations and industry. The model of railway supplier selection using BI-KM framework is situated on a horizontal structure of the organization and its technology transformation to execute the organization goal, with technology as enabler and driver (technology adoption), organization as the pr

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Munjala, Mahesh Babu. "Exploring Analytics in SAP S/4HANA Cloud: Capabilities, Integration, and Business Value." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 01 (2024): 1–13. http://dx.doi.org/10.55041/ijsrem27868.

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With the accelerated adoption of modern cloud- based enterprise resource management (ERP) systems, organizations recognize the importance of integrated analytics capabilities to drive data driven business insights and gain a competitive edge. This study explores the real-time analytics architecture of SAP S/4HANA Cloud, a leading cloud ERP system, and its potential to improve decision-making and enhance operational excellence. Existing research has primarily focused on analytics in the conventional S/4HANA system. Thus, technical documentation, industry blogs, and implementation expertise are

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Saputro, Adi, Selamet Riyadi, David David, and Eryco Muhdaliha. "Transformasi Digital dan Inovasi Model Bisnis: Strategi Meningkatkan Kinerja Operasional Berkelanjutan Berbasis Kapabilitas Dinamis." Indo-MathEdu Intellectuals Journal 6, no. 4 (2025): 5259–72. https://doi.org/10.54373/imeij.v6i4.3442.

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Digital transformation has become a core strategy to drive innovation and enhance operational performance in the era of technological disruption. This article aims to analyze the role of business digitalization in simultaneously promoting operational efficiency and business model innovation. Using a systematic literature review of more than 30 academic articles and cross-industry case studies, this study integrates the perspectives of dynamic capabilities, the balanced scorecard, and organizational ambidexterity as analytical frameworks. The findings indicate that the success of digitalization

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Chetan Sharma and Adarsh Vaid. "Converging SAP, AI, and data analytic for transformative business management." World Journal of Advanced Research and Reviews 14, no. 3 (2022): 736–61. http://dx.doi.org/10.30574/wjarr.2022.14.3.0214.

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The convergence of Artificial Intelligence (AI) and Machine Learning (ML) with Systems, Applications, and Products in Data Processing (SAP) technologies is revolutionizing enterprise operations, driving smarter decision-making and greater operational efficiency. This article examines the application of AI and ML algorithms within SAP platforms to streamline and enhance core business functions. By tapping into SAP-powered data analytic, companies can unlock valuable insights into their performance metrics, enabling data-driven decisions that elevate operational effectiveness. The paper also hig

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Kothapalli, Kanaka Rakesh Varma. "Exploring the Impact of Digital Transformation on Business Operations and Customer Experience." Global Disclosure of Economics and Business 11, no. 2 (2022): 103–14. http://dx.doi.org/10.18034/gdeb.v11i2.760.

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This study examines how digital transformation affects corporate operations and customer experience to determine its main pros and cons. Digital developments' effects on operational efficiency and customer happiness are assessed using secondary data from current research and case studies. Digital transformation enhances operational processes via automation, data analytics, and customer experience through customization, AI-powered support, and seamless integration across numerous channels. Significant challenges include high installation costs, business performance variation, and data privacy r

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Srinivasulu, K., and K. Rahul. "AI in Commerce: Innovations in Sales Optimization, Supply Chain Efficiency and Consumer Behavior Analysis." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44158.

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This research paper investigates the impact Artificial Intelligence (AI) is having on the foundational aspects of commerce sales optimization, supply chain management, and consumer behavior analysis. As organizations move into an era of enhanced competition and changing consumer needs, business leaders are now incorporating AI-driven strategies into their business models as the means for achieving operational excellence, and responding to market changes. By considering commercial applications, this research looks in to the function of AI algorithms, predictive analytics, and regression-based m

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Kathala, Gouthami. "AI-Driven Integration Tools for Mitigating API Performance Challenges: Enhancing Business Agility in the Digital Era." European Journal of Computer Science and Information Technology 13, no. 16 (2025): 96–106. https://doi.org/10.37745/ejcsit.2013/vol13n1696106.

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In today's digital landscape, businesses increasingly rely on distributed architectures and API-driven integrations to maintain competitive agility. However, performance bottlenecks and optimization challenges in API interactions can lead to operational inefficiencies, degraded customer experience, and increased costs. The implementation of AI-driven frameworks leverages advanced integration tools powered by machine learning to proactively monitor, diagnose, and optimize API performance. By incorporating real-time analytics and predictive modeling, the solution not only detects anomalies and p

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Sama, Shyamlal. "How JD Edwards EnterpriseOne Powers Operational Efficiency and Customer-Centric Strategies in Quick Service Restaurants." European Journal of Computer Science and Information Technology 13, no. 28 (2025): 114–46. https://doi.org/10.37745/ejcsit.2013/vol13n28114146.

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JD Edwards EnterpriseOne has established itself as a pivotal enterprise resource planning solution for Quick Service Restaurants, simultaneously addressing operational challenges and customer engagement imperatives in this competitive industry. This comprehensive platform creates value through five key capabilities: unifying traditionally siloed business functions into a cohesive ecosystem, enabling agile decision-making through real-time analytics, fostering customer-centricity via comprehensive data integration, building supply chain resilience while supporting menu innovation, and facilitat

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Shaileshbhai Revabhai Gothi. "Automating Data Center Lifecycle Management: A Comprehensive Framework for Enhanced Operational Excellence." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 2836–46. https://doi.org/10.32628/cseit25112748.

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Data center infrastructure forms the backbone of modern digital transformation initiatives, necessitating sophisticated management approaches throughout their lifecycle. As complexity increases, traditional manual operations have become unsustainable, leading to significant operational challenges including frequent outages, inefficient resource utilization, and security vulnerabilities. The global data center automation market is expanding rapidly, with projections indicating growth from $9.45 billion in 2024 to over $20 billion by 2028. This comprehensive article explores the evolution of dat

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Researcher. "ADVANCED FORECASTING MODELS IN ACTION: CROSS-SECTOR CASE STUDIES AND THEIR BUSINESS IMPACTS." International Journal of Engineering and Technology Research (IJETR) 9, no. 2 (2024): 10–18. https://doi.org/10.5281/zenodo.13373691.

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This article examines the implementation and impact of advanced forecasting models across three key industries: retail, finance, and energy. Through detailed case studies, we analyze how these sectors have leveraged predictive analytics to address critical business challenges. The retail case demonstrates significant improvements in inventory management, while the finance sector example showcases enhanced risk assessment and financial planning. In the energy sector, we explore how forecasting has led to improved demand prediction and increased operational efficiency. Our cross-sector analysis

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Bhati, Bharat. "Influence of Digital Transformation on Business Processes and Customer Engagement." International Journal for Research in Applied Science and Engineering Technology 13, no. 2 (2025): 102–8. https://doi.org/10.22214/ijraset.2025.66796.

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This research explores the influence of digital transformation on business operations and customer experience, focusing on its primary benefits and challenges. By analyzing secondary data from existing studies and case examples, the study evaluates how advancements in digital technology improve operational efficiency and enhance customer satisfaction. Key findings reveal that digital transformation streamlines processes through automation, harnesses data analytics for informed decision-making, and elevates customer experiences via personalization, AI-driven support, and multi-channel integrati

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Ekaette Tim, Ayodeji Babalola, Abla Akpene Kossidze, and Sai Vidhya Goriparthi. "Integrating advanced information analysis techniques to enhance operational efficiency in business administration practices." World Journal of Advanced Research and Reviews 25, no. 1 (2025): 1275–93. https://doi.org/10.30574/wjarr.2025.25.1.0157.

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Advanced techniques of information analysis, with their implementation, have become the basis of the economic efficiency of modern business management. In the face of ever-compounding complexity in markets and even more growing competition, applying data-driven tools and methodologies can have transformative power to simplify processes, optimize resource utilization, and improve decision-maker effectiveness. This article discusses how operational excellence across a number of business administration practices is driven by advanced information analysis. It elaborates on defeat analytical method

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Devika Rajhamundry. "Business Intelligence as a Strategic Planning Tool in Healthcare Organizations: A Systems Integration Approach." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 1965–72. https://doi.org/10.32628/cseit241061234.

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The integration of Business Intelligence (BI) in healthcare strategic planning has emerged as a critical factor in transforming raw data into actionable insights for executive decision-making. This article explores the comprehensive framework of BI implementation in healthcare organizations, addressing the challenges of integrating data from multiple specialized systems including Electronic Medical Records (EMR), physician credentialing, contracting management, revenue cycle operations, and quality assessment platforms. Through detailed analysis of data integration methodologies, analytical ca

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Thomas Aerathu Mathew. "Enhancing data platform observability with AI-driven metadata analytics." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 039–47. https://doi.org/10.30574/wjaets.2025.15.2.0536.

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This article explores the transformative potential of AI-driven metadata analytics for enhancing data platform observability across modern enterprise ecosystems. As organizations navigate increasingly complex data landscapes comprising cloud warehouses, orchestration tools, and visualization platforms, traditional monitoring approaches fall short of providing comprehensive visibility. The integration of artificial intelligence with metadata management emerges as a solution that enables proactive issue detection, automated root cause analysis, and predictive insights. Through examining metadata

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Venkata Sunil Kumar Majeti. "The Evolution of AI-Powered Quote-to-Cash: Transforming business operations." World Journal of Advanced Engineering Technology and Sciences 15, no. 3 (2025): 1138–43. https://doi.org/10.30574/wjaets.2025.15.3.1002.

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The integration of artificial intelligence in Quote-to-Cash (Q2C) processes has revolutionized how businesses manage their revenue operations. This technical article explores the transformative impact of AI across various aspects of Q2C, including customer relationship management, contract review systems, and document processing automation. The implementation of AI-driven solutions has demonstrated significant improvements in operational efficiency, compliance management, and customer satisfaction. Advanced technologies such as natural language processing, machine learning, and optical charact

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Fredson, Gracetiti, Babatunde Adebisi, Olushola Babatunde Ayorinde, Ekene Cynthia Onukwulu, Olugbenga Adediwin, and Alexsandra Ogadimma Ihechere. "Modernizing Corporate Governance through Advanced Procurement Practices: A Comprehensive Guide to Compliance and Operational Excellence." International Journal of Judicial Law 3, no. 1 (2024): 36–57. https://doi.org/10.54660/ijjl.2024.3.1.36-57.

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Corporate governance and procurement practices are increasingly intertwined as organizations strive for compliance, operational excellence, and competitive advantage in the modern business landscape. This paper explores how advanced procurement strategies can serve as a catalyst for modernizing corporate governance frameworks. By integrating innovative tools such as data analytics, artificial intelligence (AI), and blockchain technology, procurement functions can be transformed into drivers of strategic decision-making, risk mitigation, and regulatory compliance. Key areas of focus include the

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Hamza, Oladimeji, Anuoluwapo Collins, Adeoluwa Eweje, and Gideon Opeyemi Babatunde. "Agile-DevOps Synergy for Salesforce CRM Deployment: Bridging Customer Relationship Management with Network Automation." International Journal of Multidisciplinary Research and Growth Evaluation 4, no. 1 (2023): 668–81. https://doi.org/10.54660/.ijmrge.2023.4.1.668-681.

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The integration of Agile and DevOps methodologies has emerged as a transformative approach for optimizing processes within the telecommunications industry and business analytics domains. By prioritizing flexibility, collaboration, and continuous improvement, Agile frameworks enable telecom organizations to adapt rapidly to market changes, enhance operational efficiency, and streamline the development of services. The DevOps model, on the other hand, fosters a culture of seamless collaboration between development and operations teams, accelerating software deployment and reducing time-to-market

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Kiran Kumar Lekkala. "SAP Signavio: Revolutionizing Business Process Management in the Cloud." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 2107–18. https://doi.org/10.32628/cseit23112559.

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SAP Signavio offers a transformative cloud-based process management and workflow automation platform that enables organizations to streamline operations, reduce costs, and improve efficiency. This article explores how SAP Signavio disrupts traditional business process management paradigms through its cloud-native approach, democratizing process capabilities across organizations regardless of size. The platform's core capabilities include BPMN 2.0 process modeling, advanced analytics, end-to-end automation, and collaborative governance features. Its native integration with the broader SAP ecosy

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Desai, Darshan, and Ashish Desai. "Integrating Generative AI in Business Intelligence: A Practical Framework for Enhancing Augmented Analytics." International Journal of Mathematical, Engineering and Management Sciences 10, no. 3 (2025): 704–28. https://doi.org/10.33889/ijmems.2025.10.3.036.

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Business Intelligence (BI) workflows benefit from the improved access to insights that Generative Artificial Intelligence (GenAI) can bring, allowing for swifter democratization of data access and improved decision-making across various domains such as finance, retail, life sciences, education technology (EdTech), etc. Although existing literature discusses theoretical models or particular case studies, it does not provide a practical framework to integrate GenAI into BI. This study fills the gap by devising a pragmatic framework employing the qualitative research method featuring semi-structu

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Oluwatosin Abdul-Azeez, Alexsandra Ogadimma Ihechere, and Courage Idemudia. "Enhancing business performance: The role of data-driven analytics in strategic decision-making." International Journal of Management & Entrepreneurship Research 6, no. 7 (2024): 2066–81. http://dx.doi.org/10.51594/ijmer.v6i7.1257.

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In today’s highly competitive business landscape, organizations are increasingly turning to data-driven analytics to enhance performance and inform strategic decision-making. This approach leverages vast amounts of data, transforming it into actionable insights that drive efficiency, innovation, and growth. The role of data-driven analytics is multifaceted, encompassing predictive, prescriptive, and descriptive analytics, each contributing uniquely to the decision-making process. Predictive analytics forecasts future trends and behaviors, enabling proactive strategies. Prescriptive analytics p

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Oloruntosin Tolulope Joel and Vincent Ugochukwu Oguanobi. "Navigating business transformation and strategic decision-making in multinational energy corporations with geodata." International Journal of Applied Research in Social Sciences 6, no. 5 (2024): 801–18. http://dx.doi.org/10.51594/ijarss.v6i5.1103.

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In the dynamic landscape of multinational energy corporations, navigating business transformation and strategic decision-making requires innovative approaches. Geodata, encompassing spatial and location-based information, emerges as a pivotal asset in this endeavor. This paper outlines the integration of geodata into the fabric of energy corporations, facilitating informed decisions and operational excellence. The introduction elucidates the significance of geodata amidst evolving business paradigms within the energy sector. It explores the transformative potential of geospatial intelligence i

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Fry, Michael J., Jeffrey D. Camm, and Glenn Wegryn. "Next Lives Here: Forging Academia–Industry Partnerships in Analytics at the University of Cincinnati." INFORMS Journal on Applied Analytics 50, no. 3 (2020): 166–75. http://dx.doi.org/10.1287/inte.2020.1032.

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In 2018, the Department of Operations, Business Analytics, and Information Systems (OBAIS) in the Carl H. Lindner College of Business at the University of Cincinnati (UC) celebrated its 50th anniversary, and in 2019 the OBAIS department won the INFORMS UPS George D. Smith Prize. The OBAIS department has a long history of excellence in fostering academia-industry collaboration in the area of analytics as well as a track record of continued innovation. In this article, we summarize some of the history of the OBAIS department and describe many of the department’s innovations that enabled the depa

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Venu Gopal Avula. "Leveraging the convergence of SAP HANA's advanced data management capabilities and generative AI's predictive analytics for next-generation enterprise intelligence." World Journal of Advanced Engineering Technology and Sciences 12, no. 1 (2024): 528–41. https://doi.org/10.30574/wjaets.2024.12.1.0216.

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The modern data-driven economy demands businesses to create intelligent systems that process massive amounts of information in real time to develop operational ideas useful for strategic planning. The article details how SAP HANA data management excellence combines generative AI prediction analysis to create an advanced enterprise decision-making framework. The SAP HANA in-memory framework's big data handling features enable users to handle enormous data sets that include both structured and unstructured data. Generative AI warehouses use machine learning, natural language processing, and larg

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Adepoju, Adebusayo Hassanat, Adeoluwa Eweje, Anuoluwapo Collins, and Oladimeji Hamza. "Developing strategic roadmaps for data-driven organizations: A model for aligning projects with business goals." International Journal of Multidisciplinary Research and Growth Evaluation 4, no. 6 (2023): 1128–40. https://doi.org/10.54660/.ijmrge.2023.4.6.1128-1140.

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The rapid evolution of data-driven organizations necessitates a strategic approach to aligning projects with overarching business goals. This paper introduces a systematic model for developing strategic roadmaps tailored to the unique needs of data-centric enterprises. The model integrates principles of risk management and stakeholder alignment to ensure organizational objectives are met efficiently and sustainably. Drawing from practical applications and industry best practices, the approach emphasizes iterative planning, prioritization of high-impact initiatives, and continuous performance e

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Researcher. "THE INTEGRATION AND IMPACT OF ARTIFICIAL INTELLIGENCE IN MODERN ENTERPRISE RESOURCE PLANNING SYSTEMS: A COMPREHENSIVE REVIEW." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 79–88. https://doi.org/10.5281/zenodo.14050064.

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This comprehensive article examines the transformative integration of Artificial Intelligence (AI) within Enterprise Resource Planning (ERP) systems, analyzing its impact across various organizational domains and functional areas. The article investigates how AI technologies revolutionize traditional ERP frameworks through advanced process automation, intelligent analytics, and adaptive learning capabilities, fundamentally enhancing organizational efficiency and decision-making processes. Through detailed analysis of core applications, including automated workflow management, predictive analyt

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Bhardwaj, Abhijeet, Narender Yadav, Jay Bhatt, Om Goel, Punit Goel, and Arpit Jain. "Enhancing Business Process Efficiency through SAP BW4HANA in Order-to-Cash Cycles." Stallion Journal for Multidisciplinary Associated Research Studies 3, no. 6 (2024): 1–20. https://doi.org/10.55544/sjmars.3.6.1.

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In today’s competitive business environment, optimizing the Order-to-Cash (O2C) cycle is critical for enhancing operational efficiency and improving customer satisfaction. This paper explores the transformative role of SAP BW/4HANA in streamlining business processes within the O2C framework. SAP BW/4HANA provides a robust data warehousing solution that integrates advanced analytics and real-time data processing capabilities, enabling organizations to gain actionable insights and make informed decisions. By leveraging the capabilities of SAP BW/4HANA, businesses can effectively manage the flow

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Chukwunweike Mokogwu, Godwin Ozoemenam Achumie, Adams Gbolahan Adeleke, Ifeanyi Chukwunonso Okeke, and Chikezie Paul-Mikki Ewim. "A leadership and policy development model for driving operational success in tech companies." International Journal of Frontline Research in Multidisciplinary Studies 4, no. 1 (2024): 001–14. http://dx.doi.org/10.56355/ijfrms.2024.4.1.0029.

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In the fast-evolving landscape of technology companies, leadership plays a critical role in shaping operational policies that align with long-term business goals. This review introduces a leadership and policy development model designed to drive operational success in technology-driven organizations. The model emphasizes the importance of visionary, collaborative, and data-driven leadership in developing and implementing operational policies that not only enhance day-to-day efficiency but also support sustainable growth and innovation. The framework is built around key leadership pillars, incl

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Aaron Beldiq, Eiser, Brigitta Callula, Natasya Aprila Yusuf, and Achani Rahmania Az Zahra. "Unlocking Organizational Potential: Assessing the Impact of Technology through SmartPLS in Advancing Management Excellence." APTISI Transactions on Management (ATM) 8, no. 1 (2024): 40–48. http://dx.doi.org/10.33050/atm.v8i1.2195.

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This study aims to explore the organizational potential in facing the impact of implementing Business Intelligence System (BIS) technology using Partial Least Squares Structural Equation Modeling (SmartPLS) as the analytical tool. We conducted research on several organizations that have adopted Business Intelligence (BIS) with the goal of enhancing managerial excellence. Data collection was carried out online, involving 150 respondents from 5 organizations in Indonesia, the majority of whom are already familiar with and have implemented BIS technology in their organizations. We evaluated the i

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Harish Chakravarthy Sadu. "Demystifying continuous integration and continuous deployment for enterprise web applications." World Journal of Advanced Engineering Technology and Sciences 15, no. 3 (2025): 1122–29. https://doi.org/10.30574/wjaets.2025.15.3.1024.

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This article demystifies Continuous Integration and Continuous Deployment (CI/CD) practices within enterprise web application development. It traces their evolution from experimental approaches to essential frameworks driving software delivery excellence. The article explores foundational concepts, architectural patterns, implementation strategies, and resilience mechanisms that help organizations balance rapid delivery with system stability. It covers critical aspects including database migration strategies, multi-service coordination, chaos engineering techniques, and performance metrics tha

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Sood, Anitej Chander, and Konika Singh Dhull. "The Future of Six Sigma- Integrating AI for Continuous Improvement." International Journal of Innovative Research in Engineering and Management 11, no. 5 (2024): 8–15. http://dx.doi.org/10.55524/ijirem.2024.11.5.2.

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This study explores the incorporation of Artificial Intelligence (AI) into traditional Six Sigma's DMAIC (Define, Measure, Analyze, Improve, Control) methodology to enhance continuous process improvement and achieve significant economic growth across industries. AI’s data analysis, machine learning algorithms coupled with real-time insights can expedite problem identification in manufacturing processes before they become substantial issues – eliminating the need for human oversight by proactively identifying potential errors or bottlenecks - this reduces wastage and optimizes resource utilizat

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Nandipati, Sai Kiran. "Utilizing Pega Decisioning for Data-Driven Dispute Resolution Strategies." Journal of Artificial Intelligence & Cloud Computing 1, no. 3 (2022): 1–6. http://dx.doi.org/10.47363/jaicc/2022(1)349.

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In the complex landscape of financial services, efficient dispute resolution is paramount for maintaining customer trust and operational excellence. This study explores the application of Pega Decisioning to develop data-driven strategies for dispute resolution. Traditional methods, often characterized by manual processing and systemic inefficiencies, struggle to meet the demands of modern financial institutions. By leveraging Pega Decisioning’s advanced capabilities in predictive and adaptive analytics, ABC Bank was able to automate and optimize its dispute resolution processes. The implement

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Sekhar Midathana. "Maximizing field service efficiency with salesforce field service: A comprehensive analysis." World Journal of Advanced Engineering Technology and Sciences 15, no. 1 (2025): 871–77. https://doi.org/10.30574/wjaets.2025.15.1.0314.

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This article explores the transformative potential of Salesforce Field Service as a comprehensive solution for organizations dispatching technicians to customer locations. The global field service management landscape is experiencing profound evolution as customer expectations rise and mobile workforces expand. Salesforce Field Service emerges as a leading platform that addresses these challenges through intelligent scheduling, mobile applications, resource optimization, and real-time monitoring capabilities. Digital engagement tools including customer portals, automated communications, and un

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Sandeep Reddy Varakantham. "Data Architecture: The Backbone of Modern Supply Chain Management." World Journal of Advanced Engineering Technology and Sciences 15, no. 3 (2025): 1590–98. https://doi.org/10.30574/wjaets.2025.15.3.1093.

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Data architecture forms the fundamental backbone of modern supply chain management, providing the essential framework for how information flows throughout complex global networks. As supply chains evolve from simple logistics operations into sophisticated ecosystems requiring precise coordination, the structural organization of data becomes increasingly critical for operational success. This comprehensive examination explores the pivotal role of data architecture in enabling visibility, integration, and intelligence across supply chain functions. From master data management to advanced analyti

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