Relevant bibliographies by topics / Analytics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Analytics'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2025

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Journal articles on the topic "Analytics"

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Watson, Hugh J. "All About Analytics." International Journal of Business Intelligence Research 4, no. 1 (January 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 intelligence in general, but there are important nuances when implementing advanced analytics, such as with the data infrastructure, analytical tools, and personnel. Companies like Amazon.com, Overstock.com, Harrah’s Entertainment, and First American Corporation are exemplars that illustrate concepts and best practices.
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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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Oddleifson, Evan. "The Effects of Modern Data Analytics in Electoral Politics." Political Science Undergraduate Review 5, no. 1 (April 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. Moreover, these strategies undermine rational choice and consequently impede a country's ability to conduct democratic politics.
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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 computer-assisted analytics among HR practitioners, and thirdly advocating for standardization in the understanding of “analytical skills” within the business context, particularly within HR. METHODOLOGY: We examine business “analytical skills” through the theoretical framework of the knowledge, skills, and abilities (KSA) included in the Occupational Information Network (O*NET) content model. Using data from the O*NET database, occupations were classified into Human Resource Management (HRM) and Analytical occupations. Then, we identified the top highly required KSAs in analytical occupations and compared their levels with those of HRM occupations to pinpoint potential gaps hindering the effective utilization of HR analytics. FINDINGS: Using the O*NET database, which describes work and worker characteristics, we establish the highly required analytical KSAs in the business analytics context that might be labeled “analytical skills”. Then, the gap analyses reveal that important analytical KSAs, such as knowledge of sales and marketing, skills in operations analysis, and abilities in mathematical and inductive reasoning, are not expected from HR occupations, creating serious barriers to HR analytics development. In general, we have found that while HR practitioners possess some of the necessary analytical KSAs, they often lack in areas such as mathematics, computers, and complex problem-solving. IMPLICATIONS: Our findings underscore the need for standardization in HR analytics definitions, advocating for the adoption of the O*NET content model as a universal framework for understanding HR analytical knowledge, skills, and abilities (KSAs). By identifying critical analytical KSAs, our research can assist HR departments in improving training, recruitment, and development processes to better integrate HR analytics. Furthermore, we identify significant gaps in analytical skills among HR practitioners, offering potential solutions to bridge these gaps. From a theoretical perspective, our precise definition of HR “analytical skills” in terms of analytic KSAs can enhance research on the effects of HR analytics on organizational performance. This refined understanding can lead to more nuanced and impactful studies, providing deeper insights into how HR analytics contributes to achieving strategic business goals. ORIGINALITY AND VALUE: Our research offers three original insights. First, we establish a standard for HR analyst skills based on the O*NET content model, providing a clear framework for the essential knowledge, skills, and abilities required in HR analytics. Second, we identify significant analytical gaps among HR professionals, highlighting areas that need development and attention. Third, we recognize the necessity for closer cooperation between HR and professional analysts, emphasizing that such collaboration is crucial for maximizing the benefits of computer-assisted HR analytics. These insights ensure that HR analytics can move beyond being a management fad and have a real, lasting impact on business outcomes.
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Hwan (Mark) Lee, Seung. "EDITORIAL: ANALYTICS FOR ANALYTICS." Marketing Education Review 33, no. 3 (July 3, 2023): 177. http://dx.doi.org/10.1080/10528008.2023.2238495.

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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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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 (December 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 platforms and a small survey of subject matter experts in the field. Findings The procurement analytics landscape developed in this research suggests that the authors will continue to see major shifts in the sourcing and supply chain technology environment in the next five years. However, there currently exists a low usage of advanced procurement analytics, and data integrity and quality issues are preventing significant advances in analytics. This study identifies the need for organizations to establish a coherent approach to collection and storage of trusted organizational data that build on internal sources of spend analysis and contract databases. In addition, current ad hoc approaches to capturing unstructured data must be replaced by a systematic data governance strategy. An important element for organizations in this evolution is managing change and the need to nourish an analytic culture. Originality/value While the majority of forward-looking research and reports merely project broad technological impact of cognitive analytics and big data, much of it does not provide specific insights into functional impacts such as the impact on procurement. The analysis of this study provides us with a clear view of the potential for business analytics and cognitive analytics to be employed in procurement processes, and contributes to development of related research topics for future study. In addition, this study suggests detailed implementation strategies of emerging procurement technologies, contributing to the existing body of the literature and industry reports.
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Husamaldin, Laden, and Nagham Saeed. "Big Data Analytics Correlation Taxonomy." Information 11, no. 1 (December 25, 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 techniques. Therefore, this paper gives a design research account for formulating and proposing a step ahead to understand the relation between the analytical methods and its associated techniques. Furthermore, this paper is an attempt to clarify this uncertainty and identify the difference between analytics methods and techniques by giving clear definitions for each method and its associated techniques to integrate them later in a new correlation taxonomy based on the research approaches. Thus, the primary outcome of this research is to achieve for the first time a correlation taxonomy combining analytic methods used for big data and its recommended techniques that are compatible for various sectors. This investigation was done through studying various descriptive articles of big data analytics methods and its associated techniques in different industries.
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McMullen, Anthony. "Google Analytics http://www.google.com/analytics/." Public Services Quarterly 6, no. 1 (February 8, 2010): 21–22. http://dx.doi.org/10.1080/15228950903517415.

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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 (June 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 concentrations of THM in blood specimen of humans, methods in part further refined in the context of previous achievements analyzing samples derived from cell-culture or tissues. Challenges and solutions to tackle efficient pre-analytic sample extraction and elimination of matrix interferences are compared. Options for automatization of pre-analytic sample-preparation and comprehensive coverage of the wide thyronome concentration range are presented. Conventional immunoassay versus LC-MS/MS-based determination of total and free THM concentrations are briefly compared.
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Dissertations / Theses on the topic "Analytics"

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Weida, Petr. "Využití Google Analytics v eshopu." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-85117.

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The main aim of this work is describing and explaining the possibilities of web analytics as a tool for effective evaluation of the web and campaigns performance. The benefit appreciate everybody, who makes decision on further web development and its marketing based on measured data. The work is divided into three main parts. The first describes how set up Google Analytics for measuring the web, the second part shows how read and interpret the measured data. In the third practical part are both applied for analyzing prohifi.cz shop.
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Kruse, Gustav, Lotta Åhag, Samuel Dahlback, and Albin Åbrink. "Seco Analytics." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-414862.

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Forecasting is a powerful tool that can enable companies to save millions in revenue every year if the forecast is good enough. The problem lies in the good enough part. Many companies today use Excel topredict their future sales and trends. While this is a start it is far from optimal. Seco Analytics aim to solve this issue by forecasting in an informative and easy manner. The web application uses the ARIMA analysis method to accurately calculate the trend given any country and product area selection. It also features external data that allow the user to compare internal data with relevant external data such as GDP and calculate the correlation given the countries and product areas selected. This thesis describes the developing process of the application Seco Analytics.
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Santiteerakul, Wasana. "Trajectory Analytics." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc801885/.

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The numerous surveillance videos recorded by a single stationary wide-angle-view camera persuade the use of a moving point as the representation of each small-size object in wide video scene. The sequence of the positions of each moving point can be used to generate a trajectory containing both spatial and temporal information of object's movement. In this study, we investigate how the relationship between two trajectories can be used to recognize multi-agent interactions. For this purpose, we present a simple set of qualitative atomic disjoint trajectory-segment relations which can be utilized to represent the relationships between two trajectories. Given a pair of adjacent concurrent trajectories, we segment the trajectory pair to get the ordered sequence of related trajectory-segments. Each pair of corresponding trajectory-segments then is assigned a token associated with the trajectory-segment relation, which leads to the generation of a string called a pairwise trajectory-segment relationship sequence. From a group of pairwise trajectory-segment relationship sequences, we utilize an unsupervised learning algorithm, particularly the k-medians clustering, to detect interesting patterns that can be used to classify lower-level multi-agent activities. We evaluate the effectiveness of the proposed approach by comparing the activity classes predicted by our method to the actual classes from the ground-truth set obtained using the crowdsourcing technique. The results show that the relationships between a pair of trajectories can signify the low-level multi-agent activities.
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Mužík, Zbyněk. "Web Analytics." Master's thesis, Vysoká škola ekonomická v Praze, 2006. http://www.nusl.cz/ntk/nusl-295.

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Práce se zabývá problematikou měření ukazatelů souvisejících s provozem webových stránek a aplikací a technologickými prostředky k tomu sloužícími ? Web Analytics (WA). Hlavním cílem práce je otestovat a porovnat vybrané zástupce těchto nástrojů a podrobit je srovnání podle objektivních kriterií, dále také kritické zhodnocení možností WA nástrojů obecně. V první části se práce zaměřuje na popis různých způsobů měření provozu na WWW a definuje související metriky. Poskytuje také přehled dostupných WA nástrojů. Následně je vytvořen hodnotící model pro WA nástroje a podle něj je ohodnoceno šest zástupců těchto nástrojů. Hodnocení má podobu uživatelského testování na datech ze dvou reálných webových stránek. Majitelům těchto dvou webových stránek je učiněno doporučení pro volbu vhodného WA nástroje na základě jejich preferencí. Dalším výstupem práce jsou reporty, vygenerované testovanými nástroji, popisující aktivity na zkoumaných webových stránkách.
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Casari, Alice. "Business Analytics." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/3846/.

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Sosa, Fidel M. Eng Massachusetts Institute of Technology. "TaleBlazer analytics : automated anonymous analytics of mobile users' behavior." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91872.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 75).
TaleBlazer is an augmented-reality platform that lets users create location-based games for their mobile devices. In order to determine the efficacy and use cases for TaleBlazer games, it is necessary to capture data about user behavior. This thesis presents TaleBlazer Analytics, an automated system which collects and analyzes mobile users' behavior in TaleBlazer games. It details the development of the TaleBlazer Analytics system, comprised of the backend data collection service and the front-end data analysis user interface.
by Fidel Sosa.
M. Eng.
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Carle, William R. II. "Active Analytics: Adapting Web Pages Automatically Based on Analytics Data." UNF Digital Commons, 2016. http://digitalcommons.unf.edu/etd/629.

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Web designers are expected to perform the difficult task of adapting a site’s design to fit changing usage trends. Web analytics tools give designers a window into website usage patterns, but they must be analyzed and applied to a website's user interface design manually. A framework for marrying live analytics data with user interface design could allow for interfaces that adapt dynamically to usage patterns, with little or no action from the designers. The goal of this research is to create a framework that utilizes web analytics data to automatically update and enhance web user interfaces. In this research, we present a solution for extracting analytics data via web services from Google Analytics and transforming them into reporting data that will inform user interface improvements. Once data are extracted and summarized, we expose the summarized reports via our own web services in a form that can be used by our client side User Interface (UI) framework. This client side framework will dynamically update the content and navigation on the page to reflect the data mined from the web usage reports. The resulting system will react to changing usage patterns of a website and update the user interface accordingly. We evaluated our framework by assigning navigation tasks to users on the UNF website and measuring the time it took them to complete those tasks, one group with our framework enabled, and one group using the original website. We found that the group that used the modified version of the site with our framework enabled was able to navigate the site more quickly and effectively.
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Dibrova, Alisa. "Web analytics. Website analysis with Google Analytics and Yandex Metrics." Thesis, Malmö högskola, Fakulteten för kultur och samhälle (KS), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-22200.

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The scope of my research is web analytics. This paper describes the process of usability analysis of the website belonging to a company Sharden Hus situated in Stockholm. From the many existing tools of web analysis I chose two the most popular ones, Google Analytics and Yandex Metrics. In similar projects that I have read, the website redesign was based on both quantitative, statistical, and qualitative (user interviews, user tests) data. In contrast to the previously carried out projects on websites improvement with the help of similar tools, I decided to base the changes on the website only on quantitative data obtained with Google and Yandex counters. This was done in order to determine whether and how Google and Yandex tools can improve the website performance. And to see if web analytics counters may provide with sufficient statistical data enough for it's correct interpretation by a web analytics designer which would lead to the improvement of the web site performance.The results of my study showed that Google and Yandex counters isolated from qualitative methods can improve the website performance. In particular, the number of visits from the territory of Sweden was increased to almost double; the overall bounce rate reduced; the number of visits to the page containing order forms significantly increased.
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Edris, Sarah R. "Improving TaleBlazer analytics." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106026.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (page 61).
TaleBlazer is a platform for creating and playing augmented reality location-based mobile games. TaleBlazer Analytics is an automated system for collecting and analyzing anonymized player data from these games. This thesis presents additions and improvements made to TaleBlazer Analytics to allow for a more in-depth view of data from individual games, as well as aggregated across games. The updated system will ultimately help researchers, game designers, partner organizations, and the TaleBlazer development team in better understanding how users play TaleBlazer games.
by Sarah R. Edris.
M. Eng.
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Nau, Alexandra. "Social Media Analytics." Universität Leipzig, 2018. https://ul.qucosa.de/id/qucosa%3A31862.

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Die Arbeit untersucht insgesamt 25 kostenfreie Social Media Analytics-Werkzeuge und liefert einen Beitrag zu einer systematischen Beurteilung dieser Anwendungssystemklasse im Rahmen des Social Customer Relationship Managements.:1 Einleitung 1.1 Motivation 1.2 Problemstellung 1.3 Vorgehen 2 Grundlagen 2.1 Social Media 2.2 Social CRM 2.3 Social Media-Analys 2.4 Softwareanalyse 2.5 Prototyping 3 Analyse von Social Media-Analyse-Tools 3.1 Kurzvorstellung der einzelnen Tools 3.2 Kernfunktionalitäten kostenfreier SMA-Anwendungen 3.3 Realisierbare Anwendungsfälle im SCRM 3.4 Vergleich mit Funktionalitäten einer kostenpflichtigen SMA-Anwendung 3.5 Betrachtung von Unterschieden 4 Entwicklung einer Auswahlhilfe 4.1 Vorüberlegungen 4.2 Implementierung 4.3 Beschreibung 5 Erkenntnisse 5.1 Ergebnisse 5.2 Defizite 6 Ausblick
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Books on the topic "Analytics"

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Simon, Phil. Analytics. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119424215.

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Badiru, Adedeji B. Data Analytics. First edition. | Boca Raton, FL : CRC Press/Taylor & Francis: CRC Press, 2020. http://dx.doi.org/10.1201/9781003083146.

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Kumar, Vijay, and Mangey Ram, eds. Predictive Analytics. First edition. | Boca Raton, FL : CRC Press/Taylor & Francis Group, LLC, 2021. | Series: Advanced research in reliability and system assurance engineering: CRC Press, 2020. http://dx.doi.org/10.1201/9781003083177.

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Verma, Rakesh M., and David J. Marchette. Cybersecurity Analytics. Boca Raton, FL : CRC Press, 2020. | Series: Chapman & Hall/CRC data science series: Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429326813.

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Aden, Timo. Google Analytics. München: Carl Hanser Verlag GmbH & Co. KG, 2012. http://dx.doi.org/10.3139/9783446432826.

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Bag, Dinabandhu. Business Analytics. Abingdon, Oxon ; New York, NY : Routledge, 2017. |: Routledge, 2016. http://dx.doi.org/10.4324/9781315464695.

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Huang, Shuai, and Houtao Deng. Data Analytics. First edition. | Boca Raton : CRC Press, 2021.: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003102656.

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Gittell, Jody Hoffer, and Hebatallah Naim Ali. Relational Analytics. New York, NY : Routledge, 2021.: Routledge, 2021. http://dx.doi.org/10.4324/9781003036371.

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Kim, Jieun, Buyong Jeong, and Daejung Kim. Patent Analytics. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2930-3.

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Rabelo, Luis, Edgar Gutierrez-Franco, Alfonso Sarmiento, and Christopher Mejía-Argueta. Engineering Analytics. New York: CRC Press, 2021. http://dx.doi.org/10.1201/9781003137993.

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Book chapters on the topic "Analytics"

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Sharma, Ashish K., Durgesh M. Sharma, Neha Purohit, Saroja Kumar Rout, and Sangita A. Sharma. "Analytics Techniques: Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics." In Decision Intelligence Analytics and the Implementation of Strategic Business Management, 1–14. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-82763-2_1.

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Weber, Felix. "Business Analytics und Analytics." In Künstliche Intelligenz für Business Analytics, 1–36. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-29773-2_1.

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Sherifi, Dasantila. "Analytics." In Portable Health Records in a Mobile Society, 249–56. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19937-1_21.

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Chute, Christopher G. "Analytics." In Clinical Informatics Study Guide, 163–85. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-22753-5_8.

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Schreiber, Ian, and Brenda Romero. "Analytics." In Game Balance, 329–57. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781315156422-13.

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Sarferaz, Siar. "Analytics." In Compendium on Enterprise Resource Planning, 341–58. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93856-7_22.

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Kasthurirathne, Suranga N., and Shaun J. Grannis. "Analytics." In Clinical Informatics Study Guide, 227–39. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93765-2_16.

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Laney, Douglas B. "Analytics." In Infonomics, 80–102. New York, NY : Routledge, 2018.: Routledge, 2017. http://dx.doi.org/10.4324/9781315108650-5.

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Vasiuk, Sergei, and Vlad Dubrovskyi. "Analytics." In Running a Successful Live Service Game, 185–202. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003427056-19.

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Steinbach, Ingo, and Hesham Salama. "Analytics." In Lectures on Phase Field, 17–29. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-21171-3_2.

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AbstractThe chapter reviews the basic analytic solutions of phase-field models at the mesoscopic scale. First the phase-field equation is derived by the Clausius-Duhem relation applied to a simple phase-field functional. The concept of variational derivative, related to the gradient contribution in the phase-field functional, is introduced. The traveling wave solution, or solitonian wave solution, for the phase-field equation in 1-dimension is derived for two relevant potential functions. Finally, the relations between model parameters and physically defined material parameters are derived.
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Conference papers on the topic "Analytics"

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Scorzato, Luigi. "Responsible Analytics." In European network for Particle physics, Lattice field theory and Extreme computing, 023. Trieste, Italy: Sissa Medialab, 2024. http://dx.doi.org/10.22323/1.451.0023.

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Cai, Guoray. "Formalizing Analytical Discourse in Visual Analytics." In 2007 IEEE Symposium on Visual Analytics Science and Technology. IEEE, 2007. http://dx.doi.org/10.1109/vast.2007.4389025.

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Ng, Raymond. "Text analytics, health analytics." In 1st Europe Summer School. New York, New York, USA: ACM Press, 2017. http://dx.doi.org/10.1145/3168836.3168845.

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Freire, Juliana. "Spatio-temporal analytics, urban analytics." In 1st Europe Summer School. New York, New York, USA: ACM Press, 2017. http://dx.doi.org/10.1145/3168836.3168839.

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Lee, Seok-Won, Robin A. Gandhi, Siddharth J. Wagle, and Ajeet B. Murty. "r-AnalytiCA: Requirements Analytics for Certification & Accreditation." In 15th IEEE International Requirements Engineering Conference (RE 2007). IEEE, 2007. http://dx.doi.org/10.1109/re.2007.34.

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Fisher, Brian, and David Kasik. "Pair Analytics in a Visual Analytics Context." In Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2023. http://dx.doi.org/10.24251/hicss.2023.151.

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Panchoo, Shireen. "Learning Analytics." In the Fourth International Conference. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3234698.3234721.

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Pieper, Jan H., Julia Grace, and Stephen Dill. "Team analytics." In the SIGCHI Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1518701.1518715.

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Garofalakis, Minos. "Streaming analytics." In 1st Europe Summer School. New York, New York, USA: ACM Press, 2017. http://dx.doi.org/10.1145/3168836.3168843.

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Andrienko, Natalia, and Gennady Andrienko. "Visual analytics." In 1st Europe Summer School. New York, New York, USA: ACM Press, 2017. http://dx.doi.org/10.1145/3168836.3168840.

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Reports on the topic "Analytics"

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Gangrade, Anidhya. Sports Analytics. Ames (Iowa): Iowa State University, December 2023. http://dx.doi.org/10.31274/cc-20240624-1326.

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Jackson, Kendell. Sports Analytics. Ames (Iowa): Iowa State University, December 2022. http://dx.doi.org/10.31274/cc-20240624-1325.

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Guess, Connor G. Sports Analytics. Ames (Iowa): Iowa State University, May 2023. http://dx.doi.org/10.31274/cc-20240624-1324.

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Kramer, Mitchell. KANA Experience Analytics. Boston, MA: Patricia Seybold Group, May 2012. http://dx.doi.org/10.1571/pr05-24-12cc.

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Kramer, Mitchell. PeopleSoft CRM Analytics. Boston, MA: Patricia Seybold Group, February 2002. http://dx.doi.org/10.1571/pr2-14-02cc.

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Kramer, Mitchell. mySAP CRM Analytics. Boston, MA: Patricia Seybold Group, March 2002. http://dx.doi.org/10.1571/pr3-23-02cc.

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Turcotte, Melissa, and Juston Shane Moore. User Behavior Analytics. Office of Scientific and Technical Information (OSTI), February 2017. http://dx.doi.org/10.2172/1345176.

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Turcotte, Melissa, Francesco Sanna Passino, Juston Shane Moore, and Nicholas Heard. User Behaviour Analytics. Office of Scientific and Technical Information (OSTI), March 2019. http://dx.doi.org/10.2172/1501758.

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Industrial Analytics Corporation. Industrial Analytics Corporation. Office of Scientific and Technical Information (OSTI), January 2004. http://dx.doi.org/10.2172/828243.

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Boehmke, Brad. Understanding Business Analytics. Fort Belvoir, VA: Defense Technical Information Center, January 2015. http://dx.doi.org/10.21236/ad1000582.

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