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Dissertations / Theses on the topic 'Data-Driven Analytics'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Hahmann, Martin. "Feedback-Driven Data Clustering." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-135647.

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The acquisition of data and its analysis has become a common yet critical task in many areas of modern economy and research. Unfortunately, the ever-increasing scale of datasets has long outgrown the capacities and abilities humans can muster to extract information from them and gain new knowledge. For this reason, research areas like data mining and knowledge discovery steadily gain importance. The algorithms they provide for the extraction of knowledge are mandatory prerequisites that enable people to analyze large amounts of information. Among the approaches offered by these areas, clusteri

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Uichanco, Joline Ann Villaranda. "Data-driven optimization and analytics for operations management applications." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85695.

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Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2013.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 163-166).<br>In this thesis, we study data-driven decision making in operation management contexts, with a focus on both theoretical and practical aspects. The first part of the thesis analyzes the well-known newsvendor model bu

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Plevoets, Christina, and Rodrigo Fernandes. "Exploring the role of Big Data and Analytics : Creating Data-Driven Innovation." Thesis, Blekinge Tekniska Högskola, Institutionen för industriell ekonomi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13463.

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Purpose: The purpose of this thesis is to understand the role of big data in the innovation process and specify the conditions or scenarios where big data and innovation can join forces. Research design, approach and method: The theoretical framework used is based on the innovation framework with big data from Kusiak (2015) and it is validated by three propositions: 1) Big data analytics (BDA) gives the possibility to discover new insights, such as increase profitability, expansion of customer base and market growth, hence it is a contributor to innovation. 2) Firms are investing or plan to in

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Alam, Joy Alam. "Building business analytics capabilities to become data-driven energy retailers." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-223723.

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Carlsson, Ståbi Jenny. "Data driven marketing : How to gain relevant insights through Google Analytics." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254988.

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In this report, problems regarding the retrieving, measuring, and analysis of data when analysing marketing effects in the web analytics tool Google Analytics will be discussed. A correct setup, configuration, maintenance, campaign tracking and the understanding of the data in Google Analytics is essential to be able to achieve relevant insights. This is important since many Swedish marketing departments experience issues related to their setup of Google Analytics as well as the ongoing configuration and maintenance. A literature study has been conducted to gather information, focusing on coll

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Sim, Jisoo. "Data-Driven Park Planning: Comparative Study of Survey with Social Media Data." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/97978.

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The purpose of this study was (1) to identify visitors’ behaviors in and perceptions of linear parks, (2) to identify social media users’ behaviors in and perceptions of linear parks, and (3) to compare small data with big data. This chapter discusses the main findings and their implications for practitioners such as landscape architects and urban planners. It has three sections. The first addresses the main findings in the order of the research questions at the center of the study. The second describes implications and recommendations for practitioners. The final section discusses the limitat

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Liu, Dapeng. "Towards developing a goal-driven data integration framework for counter-terrorism analytics." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5986.

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Terrorist attacks can cause massive casualties and severe property damage, resulting in terrorism crises surging across the world; accordingly, counter-terrorism analytics that take advantage of big data have been attracting increasing attention. The knowledge and clues essential for analyzing terrorist activities are often spread across heterogeneous data sources, which calls for an effective data integration solution. In this study, employing the goal definition template in the Goal-Question-Metric approach, we design and implement an automated goal-driven data integration framework for coun

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Flatt, Taylor. "CrowdCloud: Combining Crowdsourcing with Cloud Computing for SLO Driven Big Data Analysis." OpenSIUC, 2017. https://opensiuc.lib.siu.edu/theses/2234.

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The evolution of structured data from simple rows and columns on a spreadsheet to more complex unstructured data such as tweets, videos, voice, and others, has resulted in a need for more adaptive analytical platforms. It is estimated that upwards of 80% of data on the Internet today is unstructured. There is a drastic need for crowdsourcing platforms to perform better in the wake of the tsunami of data. We investigated the employment of a monitoring service which would allow the system take corrective action in the event the results were trending in away from meeting the accuracy, budget, and

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Arkstål, Emil. "Interactive Analytics and Visualization for Data Driven Calculation of Individualized COPD Risk." Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-151925.

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Chronic obstructive pulmonary disease (COPD) is a high mortality disease, second to stroke and ischemic heart disease. This non-curable disease progressively exacerbates, leading to high personal and societal economic impact, reduced quality of life and often death. General treatment plans for COPD risk mistreating the individuals’ condition. To be effective, the treatment should be individualized following the practices of precision medicine. The aim of this thesis was to develop a data driven algorithm and system with visualization to assess individual COPD risk. With MRI body composition pr

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10

Evans, Ben Richard. "Data-driven prediction of saltmarsh morphodynamics." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/276823.

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Saltmarshes provide a diverse range of ecosystem services and are protected under a number of international designations. Nevertheless they are generally declining in extent in the United Kingdom and North West Europe. The drivers of this decline are complex and poorly understood. When considering mitigation and management for future ecosystem service provision it will be important to understand why, where, and to what extent decline is likely to occur. Few studies have attempted to forecast saltmarsh morphodynamics at a system level over decadal time scales. There is no synthesis of existing

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11

Wang, Lening. "Process and Quality Modeling in Cyber Additive Manufacturing Networks with Data Analytics." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/104655.

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A cyber manufacturing system (CMS) is a concept generated from the cyber-physical system (CPS), providing adequate data and computation resources to support efficient and optimal decision making. Examples of these decisions include production control, variation reduction, and cost optimization. A CMS integrates the physical manufacturing equipment and computation resources via Industrial Internet, which provides low-cost Internet connections and control capability in the manufacturing networks. Traditional quality engineering methodologies, however, typically focus on statistical process contr

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Bücker, Dennis. "Designing Applications for Smart Cities: A designerly approach to data analytics." Thesis, Malmö högskola, Fakulteten för kultur och samhälle (KS), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-23305.

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The purpose of this thesis is to investigate the effects of a designerly approach to data analytics. The research was conducted during the Interaction Design Master program at Malmö University in 2017 and follows a research through design approach where the material driven design process in itself becomes a way to acquire new knowledge. The thesis uses big data as design material for designers to ideate connected products and services in the context of smart city applications. More specifically, it conducts a series of material studies that show the potential of this new perspective to data a

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Koseler, Kaan Tamer. "Realization of Model-Driven Engineering for Big Data: A Baseball Analytics Use Case." Miami University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=miami1524832924255132.

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Khaghani, Farnaz. "Resilience-based Operational Analytics of Transportation Infrastructure: A Data-driven Approach for Smart Cities." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/99206.

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Studying recurrent mobility perturbations, such as traffic congestions, is a major concern of engineers, planners, and authorities as they not only bring about delay and inconvenience but also have consequent negative impacts like greenhouse gas emission, increase in fuel consumption, or safety issues. In this dissertation, we proposed using the resilience concept, which has been commonly used for assessing the impact of extreme events and disturbances on the transportation system, for high-probability low impact (HPLI) events to (a) provide a performance assessment framework for transportatio

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Amerian, Irsa. "Improving data-driven decision making through data democracy : Case study of a Swedish bank." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-105868.

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Nowadays, becoming data-driven is the vision of almost all organizations. However, achieving this vision is not as easy as it may look like and there are many factors that affect, enable, support and sustain the data-driven ecosystem in an organization. Among these factors, this study focuses on data democracy which can be defined as the intra-organizational open data that aims to empower the employees getting faster and easier access to data in order to benefit from the business insight they need without the interfere of external help. In the existing literature, while the importance of beco

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Calfa, Bruno Abreu. "Data Analytics Methods for Enterprise-wide Optimization Under Uncertainty." Research Showcase @ CMU, 2015. http://repository.cmu.edu/dissertations/575.

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This dissertation primarily proposes data-driven methods to handle uncertainty in problems related to Enterprise-wide Optimization (EWO). Datadriven methods are characterized by the direct use of data (historical and/or forecast) in the construction of models for the uncertain parameters that naturally arise from real-world applications. Such uncertainty models are then incorporated into the optimization model describing the operations of an enterprise. Before addressing uncertainty in EWO problems, Chapter 2 deals with the integration of deterministic planning and scheduling operations of a n

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Economou, Emmanuel. "How institutional pressures influence data-driven corporate communications." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/209153/1/Emmanuel_Economou_Thesis.pdf.

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This study explores the use of data to guide corporate communications, a practice of which empirical research is limited, and is the first to investigate how institutional pressures influence practitioners in their work. In-depth interviews were conducted with 15 participants from a wide range of organisations in Brisbane, Australia. Additionally, the study illustrates the current state of research on big data in corporate communication in a systematic literature review. The study’s findings indicate that institutional pressures influence data-driven corporate communications and are generally

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Xu, Haowen. "Data-driven framework for forecasting sedimentation at culverts." Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/6892.

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The increasing intensity and frequency of precipitation in recent decades, combined with the human interventions in watersheds, has drastically altered the natural regimes of water and sediment transport in watersheds over the whole contiguous United States. Sediment-transport related concerns include the sustainability of aquatic biology, the stability of the river morphology, and the security and vulnerability of various riverine structures. For the present context, the concerns are related to the acceleration of upland erosion (sediment production) and in-stream sediment-transport processes

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Notz, Pascal Markus [Verfasser], Richard [Gutachter] Pibernik, and Christoph [Gutachter] Flath. "Prescriptive Analytics for Data-driven Capacity Management / Pascal Markus Notz ; Gutachter: Richard Pibernik, Christoph Flath." Würzburg : Universität Würzburg, 2021. http://d-nb.info/123654806X/34.

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Höcker, Filip, and Finn Brand. "‘Data over intuition’ – How big data analytics revolutionises the strategic decision-making processes in enterprises." Thesis, Internationella Handelshögskolan, Jönköping University, IHH, Företagsekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-48560.

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Background: Digital technologies are increasingly transforming traditional businesses, and their pervasive impact is leading to a radical restructuring of entire industries. While the significance of generating competitive advantages for businesses utilizing big data analytics is recognized, there is still a lack of consensus of big data analytics influencing strategic decision-making in organisations. As big data and big data analytics become increasingly common, understanding the factors influencing decision-making quality becomes of paramount importance for businesses. Purpose: This thesis

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Ganss, Thorsten Peter. "Bottleneck Identification using Data Analytics to Increase Production Capacity." Thesis, KTH, Industriell produktion, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-298987.

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The thesis work develops an automated, data-driven bottleneck detection procedure based on real-world data. Following a seven-step process it is possible to determine the average as well as the shifting bottleneck by automatically applying the active period method. A detailed explanation of how to pre-process the extracted data is presented which is a good guideline for other analysists to customize the available code according to their needs. The obtained results show a deviation between the expected bottleneck and the bottleneck calculated based on production data collected in one week of fu

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Dyrhage, Max. "Incorporating a tag management system in an agile web development process to become more data-driven." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-240395.

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Web analytics are used to track and examine user behavior on websites and web applications. In order to take data driven decisions companies and organizations working with the web look to web analytics to understand their users. A piece of Javascript code that collect user behavior and information is often referred to as a tag, which can be managed through a tag management system. Tag management systems can provide structure to how a website’s users’ behaviors are being measured. This study examines how a tag management system can enable web analytics of user data to be incorporated in an agil

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Taigel, Fabian [Verfasser], Richard [Gutachter] Pibernik, and Christoph [Gutachter] Flath. "Data-driven Operations Management: From Predictive to Prescriptive Analytics / Fabian Taigel ; Gutachter: Richard Pibernik, Christoph Flath." Würzburg : Universität Würzburg, 2020. http://d-nb.info/1212798643/34.

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Peyne, Benjamin, and Ariane Chan. "Data-driven decision making in Marketing : A theoretical approach." Thesis, Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-33545.

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Customer insight is at the heart of the big data era. This revolution makesit possible to directly obtain high potential data and in large quantitiesabout customers. Thus we take note that, more than ever, a large volumeof big data is collected by companies.We observe that big data have become a necessary tool within marketing.More and more companies orient their decisions according to theinformations provided by data, with the aim of quickly having betterresults.Nevertheless, in order to integrate these big data in a better way and gaina competitive advantage, companies must face new challeng

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Aldherwi, Aiman. "Conceptualising a Procurement 4.0 Model for a truly Data Driven Procurement." Thesis, KTH, Hållbar produktionsutveckling (ML), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297583.

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Purpose - Procurement is an integrated part of the supply chain and crucial for the success of manufacturing. Many organisations have already started the digitalisation of their manufacturing processes using Industry 4.0 technologies and consequently trying to understand how this would impact the procurement function. The research purpose is to conceptualize a procurement of 4.0 model for a truly data driven procurement. Two research questions were proposed to address the model from digital capabilities and sustainability preceptive. Design/Methodology/approach - This study is based on a syste

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Sacchetti, Giacomo. "L’impatto degli Analytics: come i Big Data stanno cambiando le aziende." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

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In questa tesi affronto il mondo dei big data e di come stanno avendo impatto sulle aziende. Vengono affrontati casi di studio come Cambridge Analytica, le elezioni Americane del 2016 e la Brexit. Si affronta anche vari aspetti di gestione e estrazione dei dati negli algoritmi di suggestione dei vari provider di servizi, quali netflix, amazon etc...

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Collerà, Alessandro. "Classificazione e selezione di tecniche di visualizzazione per Big Data Analytics." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10968/.

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La tesi presenta uno studio della libreria grafica per web D3, sviluppata in javascript, e ne presenta una catalogazione dei grafici implementati e reperibili sul web. Lo scopo è quello di valutare la libreria e studiarne i pregi e difetti per capire se sia opportuno utilizzarla nell'ambito di un progetto Europeo. Per fare questo vengono studiati i metodi di classificazione dei grafici presenti in letteratura e viene esposto e descritto lo stato dell'arte del data visualization. Viene poi descritto il metodo di classificazione proposto dal team di progettazione e catalogata la galleria di graf

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Singh, Shailendra. "Smart Meters Big Data : Behavioral Analytics via Incremental Data Mining and Visualization." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35244.

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The big data framework applied to smart meters offers an exception platform for data-driven forecasting and decision making to achieve sustainable energy efficiency. Buying-in consumer confidence through respecting occupants' energy consumption behavior and preferences towards improved participation in various energy programs is imperative but difficult to obtain. The key elements for understanding and predicting household energy consumption are activities occupants perform, appliances and the times that appliances are used, and inter-appliance dependencies. This information can be extracted f

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Baitalmal, Mohammad Hamza. "A Grounded Theory Model of the Relationship between Big Data and an Analytics Driven Supply Chain Competitive Strategy." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1404511/.

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The technology for storing and using big data is evolving rapidly and those that can keep pace are likely to garner additional competitive advantages. One approach to uncovering existing practice in a manner that provides insights for building theory is the use of grounded theory. The current research employs qualitative research following a grounded theory approach to explore gap in understanding the relationship between big data (BD) and the supply chain (SC). In this study eight constructs emerged: Organizational and environmental factors, big data and supply chain analytics, alignment, dat

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Uwagbole, Solomon. "A pattern-driven corpus to predictive analytics in mitigating SQL injection attack." Thesis, Edinburgh Napier University, 2018. http://researchrepository.napier.ac.uk/Output/1538260.

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The back-end database provides accessible and structured storage for each web application's big data internet web traffic exchanges stemming from cloud-hosted web applications to the Internet of Things (IoT) smart devices in emerging computing. Structured Query Language Injection Attack (SQLIA) remains an intruder's exploit of choice to steal confidential information from the database of vulnerable front-end web applications with potentially damaging security ramifications. Existing solutions to SQLIA still follows the on-premise web applications server hosting concept which were primarily dev

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Baitalmal, Mohammad Hamza. "A Grounded Theory Model of the Relationship between Big Data and an Analytics-Driven Supply Chain Competitive Strategy." Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc1404511/.

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The technology for storing and using big data is evolving rapidly and those that can keep pace are likely to garner additional competitive advantages. One approach to uncovering existing practice in a manner that provides insights for building theory is the use of grounded theory. The current research employs qualitative research following a grounded theory approach to explore gap in understanding the relationship between big data (BD) and the supply chain (SC). In this study eight constructs emerged: Organizational and environmental factors, big data and supply chain analytics, alignment, dat

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Singhvi, Somya. "Improving farmers' and consumers' welfare in agricultural supply chains via data-driven analytics and modeling : from theory to practice." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129083.

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Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, September, 2020<br>Page 236 blank. Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 223-235).<br>The upstream parts of the agricultural supply chain consists of millions of smallholder farmers who continue to suffer from extreme poverty. The first stream of research in this thesis focuses on online agri-platforms which have been launched to connect geographically isolated markets in many developing countries. This work is in close collaboration with

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Lavassani, Mehrzad. "Reliable Information Exchange in IIoT : Investigation into the Role of Data and Data-Driven Modelling." Licentiate thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34886.

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The concept of Industrial Internet of Things (IIoT) is the tangible building block for the realisation of the fourth industrial revolution. It should improve productivity, efficiency and reliability of industrial automation systems, leading to revenue growth in industrial scenarios. IIoT needs to encompass various disciplines and technologies to constitute an operable and harmonious system. One essential requirement for a system to exhibit such behaviour is reliable exchange of information. In industrial automation, the information life-cycle starts at the field level, with data collected by s

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Garrido, Fernández Aurora. "Towards transport futures using mobile data analytics : Stakeholder identification in the city of Stockholm." Thesis, KTH, Hållbar utveckling, miljövetenskap och teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-240604.

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The use of big data in urban transport planning is unstoppably gaining momentum and with the help of strategic business partnerships and technological advancements (e.g. transport apps, mobile device location tracking, data processing) the new mobility models are evolving towards an integrated and multimodal urban mobility: Mobility as a Service (MaaS). From the generation of data by Telecom companies to transport end users, a broad range of stakeholders are involved in the data market. This tighter with the call for sustainable alternatives in passenger traffic highlights that business relati

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Chen, Longbiao. "Big data-driven optimization in transportation and communication networks." Electronic Thesis or Diss., Sorbonne université, 2018. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2018SORUS393.pdf.

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L'évolution des structures métropolitaines ont créé divers types de réseaux urbains. Parmi lesquels deux types de réseaux sont d'une grande importance pour notre vie quotidienne : les réseaux de transport correspondant à la mobilité humaine dans l'espace physique et les réseaux de communications soutenant les interactions humaines dans l'espace numérique. L'expansion rapide dans la portée et l'échelle de ces deux réseaux soulève des questions de recherche fondamentales sur la manière d’optimiser ces réseaux. Certains des objectifs principaux comprennent le provisioning de ressources à la deman

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Culumber, Janene Jones. "Physician Practice Survival: The Role of Analytics in Shaping the Future." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/7009.

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This dissertation joins an ongoing discussion in the business management and information technology literature surrounding the measurement of an organization’s business analytic capability, the benefits derived from maturing the capability and the improvements being made toward maturity. The dissertation specifically focuses on the healthcare industry in the United States and more specifically independent physician practices specializing in orthopaedics. After an extensive literature review along with expertise from industry leaders and experienced academic faculty, a sur

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Carlson, Olof, Viktor Thunmarker, and Mikael Zetterberg. "Exploring Swedish Hospitals’ Transition towards becoming more Data-Driven : A Qualitative Case Study of Two Swedish Hospitals." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-176517.

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The Swedish health care sector must improve productivity in order to deal with anincreased demand from an aging population with limited resources. In the traditiondriven health care sector, transitioning towards becoming more data-driven has beenidentified as a potential solution. This explorative qualitative case study explores howindividual employees perceive this development at two Swedish hospitals. The resultscomplement theory by presenting propositions that explains drivers and barriers ofthe transition, but also the outcomes of it as perceived by the employees. The studyprimarily conclu

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Dedge, Parks Dana M. "Defining Data Science and Data Scientist." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/7014.

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The world’s data sets are growing exponentially every day due to the large number of devices generating data residue across the multitude of global data centers. What to do with the massive data stores, how to manage them and defining who are performing these tasks has not been adequately defined and agreed upon by academics and practitioners. Data science is a cross disciplinary, amalgam of skills, techniques and tools which allow business organizations to identify trends and build assumptions which lead to key decisions. It is in an evolutionary state as new technologies with capabilities ar

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Neu, Jönsson Yvonne, and Oskar Lindström. "Värdet av data : en studie på hur skidanläggningar kan dra nytta av data." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-44497.

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I takt med digitaliseringen blir datadrivet beslutsfattande det nya normala i många branscher. Konkurrensfördelarna är allmänt kända eftersom det hjälper företag att utvecklas. Denna fallstudie syftar till att belysa de möjligheter som datadriven optimering bidrar med för skidorter när det kommer till att förbättra tjänster och anpassa skidanläggningar för framtiden. Huvudfokuset är att studera rörelsemönster hos skidåkare med hjälp av processutvinningsverktyg och andra metoder för visualisering. Detta har lett till följande forskningsfrågor: Vilken information går att utvinna ur data från lif

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Abrahams, Narzeen. "A study to determine the perception of people analytics tools to improve people management practices in selected departments within the public sector in the Western Cape." University of Western Cape, 2020. http://hdl.handle.net/11394/7401.

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Magister Commercii (Industrial Psychology) - MCom(IPS)<br>People analytics refer to people-related, data-driven, processes (e.g. trend analyses and data management) aimed at describing and evaluating the effectiveness and efficiency of people management practices and processes in support of business outcomes in order to inform and improve people management initiatives and performance as well as business decision making.

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Morselli, Luca. "Analisi e implementazione di un sistema di Data Visualization in relazione al modello organizzativo aziendale." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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Le aziende oggi sono sopraffatte dall'enorme quantitativo di dati con cui hanno a che fare: una corretta archiviazione di questi è presupposto fondamentale per consentire un'accurata rappresentazione dei dati per poter poi essere analizzati da parte dei diversi attori aziendali. Per fare ciò si ricorre all'utilizzo di sistemi di Business Intelligence in grado di fornire un supporto fondamentale lungo tutto il processo decisionale a diversi livelli. L'elaborato ha dunque come scopo principale la presentazione delle tecniche di Data Visualization a supporto di tale processo in funzione del ruol

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Varvne, Matilda, Simon Cederholm, and Anton Medbo. "The Major Challenges in DDDM Implementation: A Single-Case Study : What are the Main Challenges for Business-to-Business MNCs to Implement a Data-Driven Decision-Making Strategy?" Thesis, Internationella Handelshögskolan, Jönköping University, IHH, Företagsekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-48842.

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Over the past years, the value of data and DDDM have increased significantly as technological advancements have made it possible to store and analyze large amounts of data at a reasonable cost. This has resulted in completely new business models that has disrupt whole industries. DDDM allows businesses to rely their decisions on data, as opposed to on gut feeling. Up until this point, literature is eligible to provide a general view of what are the major challenges corporations encounter when implementing a DDDM strategy. However, as the field is still rather new, the challenges identified are

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Pereira, Filipe Dwan, and 95-99119-6508. "Uso de um método preditivo para inferir a zona de aprendizagem de alunos de programação em um ambiente de correção automática de código." Universidade Federal do Amazonas, 2018. https://tede.ufam.edu.br/handle/tede/6425.

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Submitted by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2018-06-04T13:02:42Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Filipe Dwan.pdf: 3617202 bytes, checksum: 21261ba9c1db7a40af29004bd0bb6f52 (MD5)<br>Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2018-06-04T13:02:58Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Filipe Dwan.pdf: 3617202 bytes, checksum: 21261ba9c1db7a40af29004bd0bb6f52 (MD5)<br>Made available i

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Zhao, Kaiyu. "A Model-driven Visual Analytic Framework for Local Pattern Analysis." Digital WPI, 2016. https://digitalcommons.wpi.edu/etd-dissertations/446.

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The ultimate goal of any visual analytic task is to make sense of the data and gain insights. Unfortunately, the process of discovering useful information is becoming more challenging nowadays due to the growing data scale. Particularly, the human cognitive capabilities remain constant whereas the scale and complexity of data are not. Meanwhile, visual analytics largely relies on human analytic in the loop which imposes challenge to traditional human-driven workflow. It is almost impossible to show every aspect of details to the user while diving into local region of the data to explain phenom

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Fridell, Gustav, and Chafjiri Saam Cedighi. "IT’S IN THE DATA : A multimethod study on how SaaS-businesses can utilize cohort analysis to improve marketing decision-making." Thesis, Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167620.

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Incorporating data and analytics within marketing decision-making is today crucial for a company’s success. This holds true especially for SaaS-businesses due to having a subscription-based pricing model dependent on good service retention for long- term viability and profitability. Efficiently incorporating data and analytics does have its prerequisites but can for SaaS-businesses be achieved using the analytical framework of cohort analysis, which utilizes subscription data to obtain actionable insights on customer behavior and retention patterns. Consequently, to expand upon the understandi

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Medeiros, Mauricius Munhoz de. "O impacto da capacidade de inteligência analítica de negócios na tomada de decisões na era dos grandes dados." Universidade do Vale do Rio dos Sinos, 2018. http://www.repositorio.jesuita.org.br/handle/UNISINOS/7109.

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Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2018-07-12T16:11:01Z No. of bitstreams: 1 Mauricius Munhoz de Medeiros_.pdf: 3956183 bytes, checksum: b542e87eedac0be0bf8f79f48709672f (MD5)<br>Made available in DSpace on 2018-07-12T16:11:01Z (GMT). No. of bitstreams: 1 Mauricius Munhoz de Medeiros_.pdf: 3956183 bytes, checksum: b542e87eedac0be0bf8f79f48709672f (MD5) Previous issue date: 2018-02-27<br>CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>Este estudo investigou o impacto das capacidades de inteligência analítica de negócios na expansão das capacidade

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Clemensson, Lisa. "Utan data är HR bara en funktion med en åsikt? : En kvalitativ studie om datadriven HR inom offentlig sektor." Thesis, Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-74720.

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HR-funktionen har genomgått en del förändringar under de senaste åren. Förändringarna har främst skett genom att HR har gått från att vara en personaladministrativ funktion till en allt mer strategisk funktion. Detta har ställt nya krav på HR-funktionens roll och dess arbete. Bland annat har HR behövt bli mer datadrivna. Störst utmaning har detta inneburit för HR-funktioner inom den offentliga sektorn, som till skillnad från privat sektor, fortfarande ligger efter i den datadrivna utvecklingen, och lite forskning har gjorts i den offentliga kontexten. Syftet med denna masteruppsats är därför a

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Schumm, Phillip Raymond Brooke. "Characterizing epidemics in metapopulation cattle systems through analytic models and estimation methods for data-driven model inputs." Diss., Kansas State University, 2013. http://hdl.handle.net/2097/16897.

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Doctor of Philosophy<br>Department of Electrical and Computer Engineering<br>Caterina Maria Scoglio<br>We have analytically discovered the existence of two global epidemic invasion thresholds in a directed meta-population network model of the United States cattle industry. The first threshold describes the outbreak of disease first within the core of the livestock system while the second threshold describes the invasion of the epidemic into a second class of locations where the disease would pose a risk for contamination of meat production. Both thresholds have been verified through extensive

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Otto, Philippa Jean. "An Analytical System for Determining Disciplinary Vocabulary for Data-Driven Learning: an Example from Civil Engineering." PDXScholar, 2017. https://pdxscholar.library.pdx.edu/open_access_etds/3472.

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Data-driven learning (DDL), an inductive teaching approach in which students learn through corpus interaction, has gained recent traction as way to teach specialized vocabulary in English for Specific Purposes (ESP) classes. There is little research, however, that addresses how to choose specialized vocabulary for teaching with DDL. This study addressed this gap in research by exploring the potential of a three-part analytical, corpus-based system for determining vocabulary to teach with DDL for a specific context of language use. This system included (1) identifying words that were significan

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Johansson, Antonia, and Filip Lindgren. "“Jag tror att man som företag säger sig vara ganska datadriven i sina beslut” : En kvalitativ studie om Business intelligence och datadrivenhet i ett svenskt konsultföretag." Thesis, Södertörns högskola, Institutionen för naturvetenskap, miljö och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-45639.

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In an increasingly digital world, companies need to be at the forefront of development in order to gain market share and be competitive. Therefore this qualitative case study intends to investigate how Business intelligence should be implemented to increase the technology acceptance among the employees. Furthermore, it is investigated how data-driven a consulting company in Sweden is. An important factor when Business intelligence is about to be implemented and applied are the employees and the company culture. It is important to normalize the collection of data, in order to create a data cult

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