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Journal articles on the topic 'Analytics'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Watson, Hugh J. "All About Analytics." International Journal of Business Intelligence Research 4, no. 1 (2013): 13–28. http://dx.doi.org/10.4018/jbir.2013010102.

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To understand and be successful with analytics, it is important to be precise in understanding what analytics means, the different targets or approaches that companies can take to using analytics, and the drivers that lead to the use of analytics. For companies that use advanced analytics, the keys to success include a clear business need; strong, committed sponsorship; a fact-based decision making culture; a strong data infrastructure; the right analytic tools; and strong analytical personnel in an appropriate organizational structure. These are the same factors for success for business intel

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Hnatiuk, Yaroslav. "CONTINENTAL ANALYTICS AND ANALYTIC PHILOSOPHY." Visnyk of the Lviv University, no. 54 (2024): 22–37. http://dx.doi.org/10.30970/pps.2024.54.3.

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Kalvakolanu, Sripathi, and Madhavaiah Chendragiri. "A NEW WAVE OF DIGITALIZING HR: HR ANALYTICS." International Research Journal of Human Resources and Social Sciences 5, no. 4 (2018): 103–12. https://doi.org/10.5281/zenodo.4452026.

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Analytics gained strategic importance with the use of bigdata. Emergence of more sophisticated analytical tools increased the credibility of business analytics. Gradually all organizations are making use of analytics. Organizations are quick enough to catch up the new developments and adopt the technologies that increase business efficiency. The use of analytic capabilities to analyze and develop insights on HR related data is broadly termed as HR Analytics, or People Analytics, or Human Capital Analytics. Many HR Professional organizations have recognized Analytics as an important capability

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Oddleifson, Evan. "The Effects of Modern Data Analytics in Electoral Politics." Political Science Undergraduate Review 5, no. 1 (2020): 46–52. http://dx.doi.org/10.29173/psur130.

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New implementations of data analytical processes in democratic politics deeply affect voter-representative relationships and constitute a substantive challenge to voter agency. This paper examines the effects of social media driven data analytics on voter microtargeting and electoral politics using Cambridge Analytica’s (CA) involvement in the 2016 US Presidential election and the 2010 Trinidad and Tobago General election. It finds that data-driven voter targeting strategies developed by Cambridge Analytica from 2014-2015 are substantially more effective than previously employed strategies. Mo

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Kulikowski, Konrad. "Defining analytical skills for human resources analytics: A call for standardization." Journal of Entrepreneurship, Management and Innovation 20, no. 4 (2024): 88–103. https://doi.org/10.7341/20242045.

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PURPOSE: Human resources (HR) analytics systems, powered by big data, AI algorithms, and information technology, are increasingly adopted by organizations to enhance HR’s impact on business performance. However, despite the widespread acknowledgment of the importance of “analytical skills” among HR practitioners in successfully implementing HR analytics systems, the specific nature of these skills remains unclear. This paper aims to address this ambiguity by firstly clarifying the concept of “analytical skills,” secondly identifying skill gaps that may hinder the effective utilization of compu

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Ponkin, I. V. "School of Practical Analytics: Analytical writing." Voprosy kul'turologii (Issues of Cultural Studies), no. 5 (May 29, 2023): 384–92. http://dx.doi.org/10.33920/nik-01-2305-03.

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This article is devoted to explaining the concept and meaning of applied analytical writing. The author outlines the requirements for analytical writing and explains some of them, including: analytical metacognitive distance; analytical insight; analytics maturity; evaluative and interpretive certainty; analytical fluency; analytical flexibility; analytical originality, analytical precision.

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Hwan (Mark) Lee, Seung. "EDITORIAL: ANALYTICS FOR ANALYTICS." Marketing Education Review 33, no. 3 (2023): 177. http://dx.doi.org/10.1080/10528008.2023.2238495.

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Handfield, Robert, Seongkyoon Jeong, and Thomas Choi. "Emerging procurement technology: data analytics and cognitive analytics." International Journal of Physical Distribution & Logistics Management 49, no. 10 (2019): 972–1002. http://dx.doi.org/10.1108/ijpdlm-11-2017-0348.

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Purpose The purpose of this paper is to elucidate the emerging landscape of procurement analytics. This paper focuses on the following questions: what are the current and future state of procurement analytics?; what changes in the procurement process will be required to enable integration of analytical solutions?; and what future areas of research arise when considering the future state of procurement analytics? Design/methodology/approach This paper employs a qualitative approach that relies on three sources of information: executive interviews, a review of current and emerging technology pla

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Husamaldin, Laden, and Nagham Saeed. "Big Data Analytics Correlation Taxonomy." Information 11, no. 1 (2019): 17. http://dx.doi.org/10.3390/info11010017.

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Big data analytics (BDA) is an increasingly popular research area for both organisations and academia due to its usefulness in facilitating human understanding and communication. In the literature, researchers have focused on classifying big data according to data type, data security or level of difficulty, and many research papers reveal that there is a lack of information on evidence of a real-world link of big data analytics methods and its associated techniques. Thus, many organisations are still struggling to realise the actual value of big data analytic methods and its associated techniq

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Köhrle, Josef, and Keith H. Richards. "Mass Spectrometry-Based Determination of Thyroid Hormones and Their Metabolites in Endocrine Diagnostics and Biomedical Research – Implications for Human Serum Diagnostics." Experimental and Clinical Endocrinology & Diabetes 128, no. 06/07 (2020): 358–74. http://dx.doi.org/10.1055/a-1175-4610.

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AbstractThe wide spectrum of novel applications for the LC-MS/MS-based analysis of thyroid hormone metabolites (THM) in blood samples and other biological specimen highlights the perspectives of this novel technology. However, thorough development of pre-analytical sample workup and careful validation of both pre-analytics and LC-MS/MS analytics, is needed, to allow for quantitative detection of the thyronome, which spans a broad concentration range in these biological samples.This minireview summarizes recent developments in advancing LC-MS/MS-based analytics and measurement of total concentr

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McMullen, Anthony. "Google Analytics http://www.google.com/analytics/." Public Services Quarterly 6, no. 1 (2010): 21–22. http://dx.doi.org/10.1080/15228950903517415.

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12

Isakov, Vladimir. "Legal Analytics in Public Administration." Academic Law Journal 25, no. 3 (2024): 500–516. https://doi.org/10.17150/1819-0928.2024.25(3).500-516.

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The author understands legal analytics as analytical activity in the field of law, which includes rule-making, administrative law enforcement (including control and supervision), law enforcement and human rights activities, legal science and education, legal education and re-education, legal culture (including the dissemination of legal information, legal journalism, legal media, Internet). By scope, analytics can be divided into natural science, technical and social. Legal analytics is a type of social analytics. The article reveals the role and place of legal analytics in public administrati

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Drye, Tim. "Applied predictive analytics and developing analytical talent." Journal of Direct, Data and Digital Marketing Practice 16, no. 1 (2014): 66–67. http://dx.doi.org/10.1057/dddmp.2014.39.

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LINSCHEID, M. "ChemInform Abstract: Analytical Chemistry: Organic Analytics 1990." ChemInform 22, no. 20 (2010): no. http://dx.doi.org/10.1002/chin.199120325.

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Dai, Tinglong, Kelly Gleason, Chao‐Wei Hwang, and Patricia Davidson. "Heart analytics: Analytical modeling of cardiovascular care." Naval Research Logistics (NRL) 68, no. 1 (2019): 30–43. http://dx.doi.org/10.1002/nav.21880.

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Mirzaalian, Farshid, and Elizabeth Halpenny. "Social media analytics in hospitality and tourism." Journal of Hospitality and Tourism Technology 10, no. 4 (2019): 764–90. http://dx.doi.org/10.1108/jhtt-08-2018-0078.

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Purpose The purpose of this paper is to provide a review of hospitality and tourism studies that have used social media analytics to collect, examine, summarize and interpret “big data” derived from social media. It proposes improved approaches by documenting past and current analytic practice addressed by the selected studies in social media analytics. Design/methodology/approach Studies from the past 18 years were identified and collected from five international electronic bibliographic databases. Social media analytics-related terms and keywords in the titles, keywords or abstracts were use

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Bokatenko, I. Yu, and N. V. Sidorov. "HR Analytics, People Analytics, Workforce Analytics and Talent Analytics. What is the difference between them." Normirovanie i oplata truda v promyshlennosti (Rationing and remuneration of labor in industry), no. 8 (August 1, 2021): 63–68. http://dx.doi.org/10.33920/pro-3-2108-06.

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This article presents the results of a study aimed at analyzing the concepts in the field of human resource management. An attempt is made to identify and establish differences between the concepts of HR Analytics, People Analytics, Workforce Analytics and Talent Analytics. The aim of the work is to identify the differences between modern concepts in human resource management. The relevance of this work is based on the emergence of a large number of similar concepts in the field of personnel management, which many employees and employers use as synonyms. When preparing the scientific article,

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Wang, Shouhong, and Hai Wang. "Knowledge Analytics." International Journal of Business Analytics 7, no. 4 (2020): 14–23. http://dx.doi.org/10.4018/ijban.2020100102.

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Big data has raised challenges and opportunities for the education sector. Educational analytics encompass a variety of computational techniques to process educational big data for effective teaching, learning, research, service, and administrative decision making. Learning analytics and academic analytics have been widely discussed in the literature of education; however, knowledge analytics have not been discussed in the educational analytics field. Knowledge analytics are a relatively new subject in the knowledge management area. Knowledge analytics lie outside of the definitions of learnin

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Kumar, S. Senthil, and Ms V. Kirthika. "Big Data Analytics Architecture and Challenges, Issues of Big Data Analytics." International Journal of Trend in Scientific Research and Development Volume-1, Issue-6 (2017): 669–73. http://dx.doi.org/10.31142/ijtsrd4673.

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Thomas, Deepa Mary. "A Survey on the Evolution of Data Analytics and the Future in Data Science." Volume 5 - 2020, Issue 8 - August 5, no. 8 (2020): 1699–703. http://dx.doi.org/10.38124/ijisrt20aug827.

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This paper cornerstone on the concepts of Data Analytics, different types of Data Analytics and the evolution of Data Analytics into the latest Prescriptive Data Analytic model. I hope this paper will be very helpful for everyone who wants to get a clear idea about the concepts of Data Analysis and the Data Analytics

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Васильева, Наталья Витальевна, and Людмила Андреевна Селиванова. "Predictive Analytics as Essential Level in Analytical Hierarchy Process." ЖУРНАЛ ПРАВОВЫХ И ЭКОНОМИЧЕСКИХ ИССЛЕДОВАНИЙ, no. 4 (December 15, 2021): 159–62. http://dx.doi.org/10.26163/gief.2021.61.13.023.

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В статье обоснована необходимость внедрения предиктивной аналитики, которая является современным трендом развития компаний. Описаны ключевые составляющие процесса предиктивной аналитики. Дается оценка результатов внедрения предиктивной аналитики в некоторых областях национальной экономики. We substantiate the need to introduce predictive analytics that is seen as a modern trend of business development. We describe the key components of predictive analytics process. The results of the introduction of predictive analytics in certain areas of national economy are assessed.

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Chiaburu, Dan S. "Analytics." Journal of Management Inquiry 25, no. 1 (2015): 111–15. http://dx.doi.org/10.1177/1056492615601342.

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Chinchor, N. A., J. J. Thomas, P. C. Wong, M. G. Christel, and W. Ribarsky. "Multimedia Analysis + Visual Analytics = Multimedia Analytics." IEEE Computer Graphics and Applications 30, no. 5 (2010): 52–60. http://dx.doi.org/10.1109/mcg.2010.92.

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Duan, Lian, and Ye Xiong. "Big data analytics and business analytics." Journal of Management Analytics 2, no. 1 (2015): 1–21. http://dx.doi.org/10.1080/23270012.2015.1020891.

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., Yogesh R. Jadhav. "GAP-ANALYTICS (GEOLOCATION AND PLACES-ANALYTICS)." International Journal of Research in Engineering and Technology 05, no. 01 (2016): 39–43. http://dx.doi.org/10.15623/ijret.2016.0501007.

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Shahril Khuzairi, Nur Maisarah, Manjit Singh Sidhu, and Zaihisma Che Cob. "Learning Analytics and Teaching Analytics: The Similarities and Differences." International Journal of Humanities, Management and Social Science 3, no. 2 (2020): 52–58. http://dx.doi.org/10.36079/lamintang.ij-humass-0302.135.

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Analytics in education which constitutes of Learning Analytics and Teaching Analytics arouses great attention among researchers and practitioners in the current climate. The use of analytics in education enables educational data to be collected and analysed to serve the needs of all stakeholders to improve the educational process. The present paper gives an overview of Learning Analytics and Teaching Analytics and explores its similarities and differences, as well as the confusion that has been raised between the two defined terms. Alongside, the analytics selection flowchart presented in this

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Faiyaad, Chisis Mohammed, and Abayomi Bin Hakim Sadiki. "How healthcare industry in Arabs can use data science for sustainable healthcare practices." Business & IT XII, no. 1 (2022): 184–92. http://dx.doi.org/10.14311/bit.2022.01.22.

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To date, the healthcare business hasn't fully understood the prospective bene?ts to be acquired from big data analytics. Although the continuously growing body of academic investigation on large data analytics is mainly technology-oriented, a clear understanding of the strategic implications of big data is urgently needed. To handle the absence, this particular analysis examines the historical development, architectural style, and portion functionalities of big data analytics. From content evaluation of twenty six BDA implementation instances in healthcare, we could determine five big data ana

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Thirathon, Usarat, Bernhard Wieder, and Maria-Luise Ossimitz. "Determinants of analytics-based managerial decisionmaking." International Journal of Information Systems and Project Management 6, no. 1 (2022): 27–40. http://dx.doi.org/10.12821/ijispm060102.

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This study investigates how managerial decision-making is influenced by Big Data analytics, analysts’ interaction skills and quantitative skills of senior and middle managers. The results of a cross-sectional survey of senior IT managers reveal that Big Data analytics (BDA) creates an incentive for managers to base more of their decisions on analytic insights. However, we also find that interaction skills of analysts and – even more so – managers’ quantitative skills are stronger drivers of analytics-based decision-making. Finally, our analysis reveals that, contrary to mainstream perceptions,

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Iyer, Lakshmi S., and Rajeshwari M. Raman. "Intelligent Analytics." International Journal of Business Intelligence Research 2, no. 1 (2011): 31–45. http://dx.doi.org/10.4018/jbir.2011010103.

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Organizations use web analytic tools and technologies to measure, collect, analyze, and report web usage data to help optimize websites. Traditionally, most of this data tends to be non-transactional and non-identifiable. In this regard, there has not been much integration with transactional data that is collected, stored, analyzed, and reported through Business Intelligence (BI). Emerging trends in web analytics provide organizations the ability to aggregate and analyze web analytics data with transactional data to provide valuable insights for building better customer relationship strategies

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Houtmeyers, Kobe C., Arne Jaspers, and Pedro Figueiredo. "Managing the Training Process in Elite Sports: From Descriptive to Prescriptive Data Analytics." International Journal of Sports Physiology and Performance 16, no. 11 (2021): 1719–23. http://dx.doi.org/10.1123/ijspp.2020-0958.

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Elite sport practitioners increasingly use data to support training process decisions related to athletes’ health and performance. A careful application of data analytics is essential to gain valuable insights and recommendations that can guide decision making. In business organizations, data analytics are developed based on conceptual data analytics frameworks. The translation of such a framework to elite sport may benefit the use of data to support training process decisions. Purpose: The authors aim to present and discuss a conceptual data analytics framework, based on a taxonomy used in bu

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Kurniawan, Candra. "A Survey on Big Data Analytics Model." ITEJ (Information Technology Engineering Journals) 4, no. 1 (2019): 1–13. http://dx.doi.org/10.24235/itej.v4i1.46.

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Topic about big data analytics have received a lot of attention and interest at this time. There are many topics can be discussed related to the analytical model, tools, and technology used. Big data analytics model involves many processes with various technologies used. Skills in handling big data, extracting mining, and developing insight are needed in applying big data analytics. Suitable analytical hardware and software also needed in decision making. Big data analytics is a key to a business strategy, but only a small portion of big data is currently used to support their business strateg

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Sharma, Manu, and Sudhanshu Joshi. "Online Advertisement Using Web Analytics Software." International Journal of Business Analytics 7, no. 2 (2020): 13–33. http://dx.doi.org/10.4018/ijban.2020040102.

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This article describes a analytic-hierarchy-process (AHP) application to identify and evaluate the best online advertising analytics software. This technique is multi-criteria and used in this study by comparing the top four web advertising analytics software. AHP uses pair-wise comparison of matrices. There are six criteria identified for evaluation: Ad scheduling, ad targeting, creative banner rotation, features, performance, cost and for each criterion, a matrix of pair-wise comparison with web-analytics software i.e. Google analytics, Accenture Analytics, Funnel and, Moat Analytics were ev

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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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Chahal, Ayushi, Preeti Gulia, and Nasib Singh Gill. "Different analytical frameworks and bigdata model for internet of things." Indonesian Journal of Electrical Engineering and Computer Science 25, no. 2 (2022): 1159. http://dx.doi.org/10.11591/ijeecs.v25.i2.pp1159-1166.

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Sensor devices used in internet of things (IoT) enabled environment produce large amount of data. This data plays a major role in bigdata landscape. In recent years, correlation, and implementation of bigdata and IoT is being extrapolated. Nowadays, predictive analytics is gaining attention of many researchers for big IoT data analytics. This paper summarizes different sort of IoT analytical platforms which consist in-built features for further use in machine learning, MATLAB, and data security. It emphasizes on different machine learning algorithms that plays important role in big IoT data an

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Chahal, Ayushi, Preeti Gulia, and Nasib Singh Gill. "Different analytical frameworks and bigdata model for internet of things." Indonesian Journal of Electrical Engineering and Computer Science 25, no. 2 (2022): 1159–66. https://doi.org/10.11591/ijeecs.v25.i2.pp1159-1166.

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Sensor devices used in internet of things (IoT) enabled environment produce large amount of data. This data plays a major role in bigdata landscape. In recent years, correlation, and implementation of bigdata and IoT is being extrapolated. Nowadays, predictive analytics is gaining attention of many researchers for big IoT data analytics. This paper summarizes different sort of IoT analytical platforms which consist in-built features for further use in machine learning, MATLAB, and data security. It emphasizes on different machine learning algorithms that plays important role in big IoT data an

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Vorobets, Yevhen, Alona Khmeliuk, Olena Moshkovska, Vali Isa Valiyev, and Oksana Marukhlenko. "THE ROLE OF DATA ANALYTICS IN MAKING MANAGEMENT DECISIONS BY THE LOGISTICS INTERMEDIARIES." Financial and credit activity problems of theory and practice 4, no. 57 (2024): 185–96. http://dx.doi.org/10.55643/fcaptp.4.57.2024.4422.

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Data analytics plays a crucial role in increasing the effectiveness of management decisions by the logistics of intermediaries. The aim of the article is to identify the extent to which the quality of data analytics affects the effectiveness of decision-making in the logistics intermediaries, in particular, the speed of delivery of the studied companies.The study employed regression and correlation analysis to identify key influencing factors in terms of data analytics on the effectiveness of management decisions of the logistics intermediaries. The significance of investment in the qualificat

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Godbless Ocran, Samuel Omokhafe Yusuf, Peprah Owusu, Enis Agyeman Boateng, Sylvester Obeng Krampah, and Adedamola Hadassah Paul-Adeleye. "AI-driven business analytics for SMES: Unlocking value through predictive and prescriptive analytic." International Journal of Science and Research Archive 13, no. 1 (2024): 3009–22. http://dx.doi.org/10.30574/ijsra.2024.13.1.2001.

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Introduction: With an emphasis on predictive and prescriptive analytics, this study examines the revolutionary implications of AI-driven analytics on small and medium-sized organizations (SMEs). SMEs play a crucial role in the global economy and require advanced solutions to improve decision-making and operational efficiency. The research aims to explore how AI-powered analytics, particularly in predictive and prescriptive forms, can add value to SMEs by enhancing demand forecasting, customer behavior insights, and financial planning. To determine how AI-driven analytics might affect SMEs, a t

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Varenko, Volodymyr. "OPERATIONAL (ONLINE) ANALYTICS: REALITIES AND PROSPECTS." Scientific journal “Library Science. Record Studies. Informology”, no. 1 (April 23, 2021): 35–41. http://dx.doi.org/10.32461/2409-9805.1.2021.229852.

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The goal of the work. The scientific problem is covered in order to systematize, generalize new knowledge about modern analytical technologies in terms of the present and prospects for their development. The research scientific novelty of the work lies in the generalization and systematization of new knowledge about operational analytics in terms of the present and prospects for its development within one study. Conclusions. The article highlights the current views of researchers on operational analytics and its information technology - Big Data technology. The works of famous experts - Bill F

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ZENKINA, Irina V. "Business analysis and business analytics: Development in the context of digitalization." Economic Analysis: Theory and Practice 22, no. 4 (2023): 646–71. http://dx.doi.org/10.24891/ea.22.4.646.

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Subject. The article addresses the analytical support for change management in conditions of orientation of economic entities to sustainable development and digital transformation of business. Objectives. The purpose is to identify modern features of business analysis, the content of the main types of business analytics, and the impact of digitalization processes on analytical activities development. Methods. The study draws on research methods, like analysis, synthesis, comparison, generalization, abstraction, systemic, strategic, and risk-oriented approaches. Results. The paper reveals the c

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Voronova, E. Yu, and A. A. Vekshina. "Improving the organization of cost analysis in a digital environment." Economics and Management 29, no. 2 (2023): 141–49. http://dx.doi.org/10.35854/1998-1627-2023-2-141-149.

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Aim. The presented study aims to substantiate the need to use digital technologies in analytics to make effective management decisions and ensure cost reduction.Tasks. The authors determine the place of a digital analytics platform in cost analysis; identify key factors in the implementation of the platform; describe the capabilities of the tools provided by the analytics platform and how they can be used in the cost management process.Methods. This study uses general scientific methods; the results are summarized through tabular and graphical presentation; four groups of data analysis methods

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Cho, Minseok, Michael Cottingham, Billy Hawkins, and Don Lee. "Sport Analytics Business: Exploring Fan Engagement on Analytical Content." IJASS(International Journal of Applied Sports Sciences) 35, no. 2 (2023): 201–14. http://dx.doi.org/10.24985/ijass.2023.35.2.201.

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With the emerging trend of technological advancement in sport media production, sport analytics has provided fan-oriented game contents through multimedia platforms. This study aims to empirically investigate sport fans’ perceptions toward sport analytics contents (i.e., statistics, video, data visualization, decision-aid) by exploring their impact on fan engagement (i.e., information, entertainment, personal identity, social interaction) and employing the uses and gratifications theory. Using multiple regressions, this study found that sport fans are more likely to consume statistics and vide

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Yadav, Neeta, and Neelendra Badal. "Analytical Study of Data Analytics and its Challenges." International Journal of Computer Applications 186, no. 44 (2024): 43–46. http://dx.doi.org/10.5120/ijca2024924081.

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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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Pamisetty, Vamsee. "Big Data and Predictive Analytics in Government Finance: Transforming Fraud Detection and Fiscal Oversight." International Journal of Engineering and Computer Science 10, no. 12 (2021): 25731–55. https://doi.org/10.18535/ijecs.v10i12.4680.

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Governments around the world are experimenting with Big Data and predictive analytics. They deploy various software applications like predictive policing, fraud detection, and capacity demand prediction while at the same time developing and investing in broader data analytical infrastructure and analytical skill sets. Implementing Big Data and predictive analytics can be a challenging endeavor, however, as these analytics often rely on open-source algorithms that are unsupervised and black-boxed. Equally challenging is how government institutions endeavor to use a waterfall approach from explo

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Papadaki, Maria-Evangelia, Nicolas Spyratos, and Yannis Tzitzikas. "Towards Interactive Analytics over RDF Graphs." Algorithms 14, no. 2 (2021): 34. http://dx.doi.org/10.3390/a14020034.

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The continuous accumulation of multi-dimensional data and the development of Semantic Web and Linked Data published in the Resource Description Framework (RDF) bring new requirements for data analytics tools. Such tools should take into account the special features of RDF graphs, exploit the semantics of RDF and support flexible aggregate queries. In this paper, we present an approach for applying analytics to RDF data based on a high-level functional query language, called HIFUN. According to that language, each analytical query is considered to be a well-formed expression of a functional alg

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Aafreen, Qureshi, and Gaurav Indra Dr. "Machine Learning Driven Edge Analytics for Healthcare: Problems, Difficulties, Future Directions, and Applications-A Review." International Journal of Innovative Science and Research Technology 7, no. 12 (2023): 1427–41. https://doi.org/10.5281/zenodo.7525315.

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With the use of edge technology, cloud resources (particularly computing, storage, and network) will be made available in close proximity to edge devices, or smart gadgets where data is generated and consumed. Edge computing and edge analytics are two new ideas in edge technology that have emerged as a result of computer and application integration in edge devices. To examine the information produced through edge gadgets, edge analytics employs a number of methods or algorithms. The development of edge analytics has made the edge gadgets a whole set. Edge analytics is currently unable to fully

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Attaran, Mohsen, and Sharmin Attaran. "The Rise of Embedded Analytics." International Journal of Business Intelligence Research 9, no. 1 (2018): 16–37. http://dx.doi.org/10.4018/ijbir.2018010102.

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This article describes how in today's hyper-competitive environment, business leaders around the world are using analytics technologies to create business values, and to gain a better understanding of their customer's needs and wants. However, traditional business analytics are undergoing major changes. The Internet revolution, cloud computing, and the evolution to self-service analytics have all contributed to the changing dimensions of business intelligence. To compete effectively in a digitally driven world, business leaders must understand and address the critical shifts taking place in th

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Wise, Alyssa, Yuting Zhao, and Simone Hausknecht. "Learning Analytics for Online Discussions: Embedded and Extracted Approaches." Journal of Learning Analytics 1, no. 2 (2014): 48–71. http://dx.doi.org/10.18608/jla.2014.12.4.

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This paper describes an application of learning analytics that builds on an existing research program investigating how students contribute and attend to the messages of others in asynchronous online discussions. We first overview the E-Listening research program and then explain how this work was translated into analytics that students and instructors could use to reflect on their discussion participation. Two kinds of analytics were designed: some embedded in the learning environment to provide students with real-time information on their activity in-progress; and some extracted from the lea

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Agrawal, Deepak. "Analytics based decision making." Journal of Indian Business Research 6, no. 4 (2014): 332–40. http://dx.doi.org/10.1108/jibr-09-2014-0062.

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Purpose – This paper aims to trace the history, application areas and users of Classical Analytics and Big Data Analytics. Design/methodology/approach – The paper discusses different types of Classical and Big Data Analytical techniques and application areas from the early days to present day. Findings – Businesses can benefit from a deeper understanding of Classical and Big Data Analytics to make better and more informed decisions. Originality/value – This is a historical perspective from the early days of analytics to present day use of analytics.

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Brock, Timothy R. "Performance Analytics: The Missing Big Data Link Between Learning Analytics and Business Analytics." Performance Improvement 56, no. 7 (2017): 6–16. http://dx.doi.org/10.1002/pfi.21701.

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