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1

Tran, Viet-Trung. "Scalable data-management systems for Big Data." Phd thesis, École normale supérieure de Cachan - ENS Cachan, 2013. http://tel.archives-ouvertes.fr/tel-00920432.

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Big Data can be characterized by 3 V's. * Big Volume refers to the unprecedented growth in the amount of data. * Big Velocity refers to the growth in the speed of moving data in and out management systems. * Big Variety refers to the growth in the number of different data formats. Managing Big Data requires fundamental changes in the architecture of data management systems. Data storage should continue being innovated in order to adapt to the growth of data. They need to be scalable while maintaining high performance regarding data accesses. This thesis focuses on building scalable data manage
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Tudoran, Radu-Marius. "High-Performance Big Data Management Across Cloud Data Centers." Electronic Thesis or Diss., Rennes, École normale supérieure, 2014. http://www.theses.fr/2014ENSR0004.

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La puissance de calcul facilement accessible offerte par les infrastructures clouds, couplés à la révolution du "Big Data", augmentent l'échelle et la vitesse auxquelles l'analyse des données est effectuée. Les ressources de cloud computing pour le calcul et le stockage sont répartis entre plusieurs centres de données de par le monde. Permettre des transferts de données rapides devient particulièrement important dans le cadre d'applications scientifiques pour lesquels déplacer le traitement proche de données est coûteux voire impossible. Les principaux objectifs de cette thèse consistent à ana
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Kalibjian, Jeff. ""Big Data" Management and Security Application to Telemetry Data Products." International Foundation for Telemetering, 2013. http://hdl.handle.net/10150/579664.

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ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV<br>"Big Data" [1] and the security challenge of managing "Big Data" is a hot topic in the IT world. The term "Big Data" is used to describe very large data sets that cannot be processed by traditional database applications in "tractable" periods of time. Securing data in a conventional database is challenge enough; securing data whose size may exceed hundreds of terabytes or even petabytes is even mo
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4

Luchentsova. "BIG DATA FOR REGIONAL AND STATE MANAGEMENT." Thesis, Київ 2018, 2018. http://er.nau.edu.ua/handle/NAU/33808.

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TREVISAN, MARTINO. "Big Data for Traffic Monitoring and Management." Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2726624.

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The last two decades witnessed tremendous advances in the Information and Com- munications Technologies. Beside improvements in computational power and storage capacity, communication networks carry nowadays an amount of data which was not envisaged only few years ago. Together with their pervasiveness, network complexity increased at the same pace, leaving operators and researchers with few instruments to understand what happens in the networks, and, on the global scale, on the Internet. Fortunately, recent advances in data science and machine learning come to the res- cue of network a
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Laurila, M. (Mikko). "Big data in Finnish financial services." Bachelor's thesis, University of Oulu, 2017. http://urn.fi/URN:NBN:fi:oulu-201711243156.

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This thesis aims to explore the concept of big data, and create understanding of big data maturity in the Finnish financial services industry. The research questions of this thesis are “What kind of big data solutions are being implemented in the Finnish financial services sector?” and “Which factors impede faster implementation of big data solutions in the Finnish financial services sector?”. Big data, being a concept usually linked with huge data sets and economies of scale, is an interesting topic for research in Finland, a market in which the size of data sets is somewhat limited by the si
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Flike, Felix, and Markus Gervard. "BIG DATA-ANALYS INOM FOTBOLLSORGANISATIONER En studie om big data-analys och värdeskapande." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20117.

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Big data är ett relativt nytt begrepp men fenomenet har funnits länge. Det går att beskriva utifrån fem V:n; volume, veracity, variety, velocity och value. Analysen av Big Data har kommit att visa sig värdefull för organisationer i arbetet med beslutsfattande, generering av mätbara ekonomiska fördelar och förbättra verksamheten. Inom idrottsbranschen började detta på allvar användas i början av 2000-talet i baseballorganisationen Oakland Athletics. Man började värva spelare baserat på deras statistik istället för hur bra scouterna bedömde deras förmåga vilket gav stora framgångar. Detta ledde
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Rystadius, Gustaf, David Monell, and Linus Mautner. "The dynamic management revolution of Big Data : A case study of Åhlen’s Big Data Analytics operation." Thesis, Jönköping University, Internationella Handelshögskolan, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-48959.

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Background: The implementation of Big Data Analytics (BDA) has drastically increased within several sectors such as retailing. Due to its rapidly altering environment, companies have to adapt and modify their business strategies and models accordingly. The concepts of ambidexterity and agility are said to act as mediators to these changes in relation to a company’s capabilities within BDA. Problem: Research within the respective fields of dynamic mediators and BDAC have been conducted, but the investigation of specific traits of these mediators, their interconnection and its impact on BDAC is
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Medlej, Maguy. "Big data management for periodic wireless sensor networks." Thesis, Besançon, 2014. http://www.theses.fr/2014BESA2029/document.

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Les recherches présentées dans ce mémoire s’inscrivent dans le cadre des réseaux decapteurs périodiques. Elles portent sur l’étude et la mise en oeuvre d’algorithmes et de protocolesdistribués dédiés à la gestion de données volumineuses, en particulier : la collecte, l’agrégation etla fouille de données. L’approche de la collecte de données permet à chaque noeud d’adapter sontaux d’échantillonnage à l’évolution dynamique de l’environnement. Par ce modèle le suréchantillonnageest réduit et par conséquent la quantité d’énergie consommée. Elle est basée surl’étude de la dépendance de la variance
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Weibl, Johannes [Verfasser]. "Managing Data Resources in the Era of Big Data / Johannes Weibl." Berlin : epubli, 2020. http://d-nb.info/1204318557/34.

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Su, Yu. "Big Data Management Framework based on Virtualization and Bitmap Data Summarization." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1420738636.

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12

Zarate, Santovena Alejandro. "Big data : evolution, components, challenges and opportunities." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/80667.

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Thesis (S.M. in Management of Technology)--Massachusetts Institute of Technology, Sloan School of Management, 2013.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 122-126).<br>This work reviews the evolution and current state of the "Big Data" industry, and to understand the key components, challenges and opportunities of Big Data and analytics face in today business environment, this is analyzed in seven dimensions: Historical Background. The historical evolution and milestones in data management that eventually led to what we know today as Big Data. What
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SHARMA, GAURAV KUMAR. "AI & BIG DATA IN FINANCIAL SERVICES." Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18335.

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Over the past few years, technology has altered the operating psychology of companies. Artificial Intelligence (AI) is becoming increasingly important and in demand, and the financial sector is steadily turning its focus to AI. In a variety of ways, financial institutions are experimenting with and integrating technology. Artificial Intelligence is improving and becoming smarter every day. Investment management companies have embraced Artificial Intelligence at a much faster rate than other industries. This is due to the fact that the financial sector still relies heavily on human involv
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Sang, Lin. "Social Big Data and Privacy Awareness." Thesis, Uppsala universitet, Institutionen för informatik och media, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-242444.

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Based on the rapid development of Big Data, the data from the online social network becomea major part of it. Big data make the social networks became data-oriented rather than social-oriented. Taking this into account, this dissertation presents a qualitative study to research howdoes the data-oriented social network affect its users’ privacy management for nowadays. Within this dissertation, an overview of Big Data and privacy issues on the social network waspresented as a background study. We adapted the communication privacy theory as a frameworkfor further analysis how individuals manage t
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Chitondo, Pepukayi David Junior. "Data policies for big health data and personal health data." Thesis, Cape Peninsula University of Technology, 2016. http://hdl.handle.net/20.500.11838/2479.

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Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2016.<br>Health information policies are constantly becoming a key feature in directing information usage in healthcare. After the passing of the Health Information Technology for Economic and Clinical Health (HITECH) Act in 2009 and the Affordable Care Act (ACA) passed in 2010, in the United States, there has been an increase in health systems innovations. Coupling this health systems hype is the current buzz concept in Information Technology, „Big data‟. The prospects of big data are full of potential, eve
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Teske, Alexander. "Automated Risk Management Framework with Application to Big Maritime Data." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38567.

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Risk management is an essential tool for ensuring the safety and timeliness of maritime operations and transportation. Some of the many risk factors that can compromise the smooth operation of maritime activities include harsh weather and pirate activity. However, identifying and quantifying the extent of these risk factors for a particular vessel is not a trivial process. One challenge is that processing the vast amounts of automatic identification system (AIS) messages generated by the ships requires significant computational resources. Another is that the risk management process partially r
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Vahedian, Khezerlou Amin. "Mining big mobility data for large urban event analytics." Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/7039.

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This thesis seeks to formulate concepts and develop methods that facilitate the mining of urban big mobility data. Specifically, the aim of the formulations and developed methods is to identify and predict certain events that occur as a result of urban mobility. This thesis, studies unexpected gathering and dispersal events. A Gathering event is the process of an unusually large number of moving objects (e.g. taxi) arriving at the same area within a short period of time. It is important for city management to identify emerging gathering events which might cause public safety or sustainability
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18

Smeda, Jorina. "Benefits, business considerations and risks of big data." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/96684.

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Thesis (MComm)--Stellenbosch University, 2015.<br>ENGLISH ABSTRACT: Big data is an emerging technology and its use holds great potential and benefits for organisations. The governance of this technology is something that is still a big concern and as aspect for which guidance to organisations wanting to use this technology is still lacking. In this study an extensive literature review was conducted to identify and define the business imperatives distinctive of an organisation that will benefit from the use of big data. The business imperatives were identified and defined based on the ch
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Kanani, Saleh. "A method to evaluate database management systems for Big Data : focus on spatial data." Thesis, Luleå tekniska universitet, Datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-74172.

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Big data of type spatial is growing exponentially with the highest rate due to extensive growth in usage of sensors, IoT and mobile devices’ spatial data generation, therefore maintaining, processing and using such data efficiently, effectively with high performance has become one of the top priorities for Database management system providers, hence spatial database features and datatypes have become serious criteria in evaluating database management systems that are supposed to work as the back-end for spatial applications and services. With exponential growth of data and introducing of new t
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Nardi, Federico. "Big Data: storia, sviluppo ed impatto socio-economico." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017.

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La finalità di questo scritto sarà quella di analizzare la storia e lo sviluppo dei Big Data, corredando il tutto con diversi esempi, di differenti settori, proprio per evidenziare ed esaminare al meglio (in termini tecnici e socio-economici) la vastità di questo fenomeno destinato a cambiare il modo di percepire la realtà dell'essere umano e la sua logica costantemente alla ricerca di una causalità. Soffermandosi inizialmente sulla spiegazione del termine stesso, verrà illustrata la nascita della parola Big Data" e i suoi molteplici campi d'utilizzo, proseguendo con la sua storia e il suo
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Bhagattjee, Benoy. "Emergence and taxonomy of big data as a service." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90709.

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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 82-83).<br>The amount of data that we produce and consume is growing exponentially in the modem world. Increasing use of social media and new innovations such as smartphones generate large amounts of data that can yield invaluable information if properly managed. These large datasets, popularly known as Big Data, are difficult to manage using traditional
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Chaudhuri, Abon. "Geometric and Statistical Summaries for Big Data Visualization." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1382235351.

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23

Gleue, Christoph [Verfasser]. "Data Mining und Big Data Analytics : semantische Suche, Prognose und Entscheidungsunterstützung mit Künstlichen Neuronalen Netzen / Christoph Gleue." Hannover : Gottfried Wilhelm Leibniz Universität Hannover, 2019. http://d-nb.info/1188406469/34.

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24

Franceschini, Davide. "Panoramica sull'utilizzo etico dei Big Data." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/13809/.

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In questa tesi mi sono occupato di Big Data. Che cosa sono, perchè sono importanti, che prospettive di utilizzo e di crescita hanno, da chi vengono utilizzati e a quali scopi. In particolare poi, mi sono soffermato sulle leggi che ne regolamentano gli usi. Quali norme in vigore ed in via di adozione sono presenti nel contesto nazionale e continentale. Un'attenzione particolare l'ho dedicata ad alcune grandi forze economiche che perseguono i propri interessi grazie alla rete. Di queste ultime ho raccontato in che modo si agevolano grazie ai Big Data rispetto alle concorrenti e di come, a vol
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Nesello, Priscila. "Implicações do fenômeno big data na análise para inteligência estratégica." reponame:Repositório Institucional da UCS, 2014. https://repositorio.ucs.br/handle/11338/822.

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Uma grande quantidade de dados é produzida diariamente por operações comerciais e financeiras, mídias sociais e dispositivos móveis, sensores e outros equipamentos inseridos no mundo físico. Este fenômeno deu origem ao termo big data, e seus efeitos podem ser percebidos por empresas, ciência e governo. Entretanto, é a inteligência estratégica, não a informação, que auxilia gerentes a extrair valor dos grandes volumes de dados. Para isto, é necessário transformar a informação dispersa no ambiente em conhecimento estruturado e útil à tomada de decisão nas organizações. Este é um processo complex
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Silva, Dilshan. "WikiSensing : a collaborative sensor management system with trust assessment for big data." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/24792.

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Big Data for sensor networks and collaborative systems have become ever more important in the digital economy and is a focal point of technological interest while posing many noteworthy challenges. This research addresses some of the challenges in the areas of online collaboration and Big Data for sensor networks. This research demonstrates WikiSensing (www.wikisensing.org), a high performance, heterogeneous, collaborative data cloud for managing and analysis of real-time sensor data. The system is based on the Big Data architecture with comprehensive functionalities for smart city sensor data
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Xu, Luna. "A Workload-aware Resource Management and Scheduling System for Big Data Analysis." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/87469.

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The big data era has driven the needs for data analysis in every aspect of our daily lives. With the rapid growth of data size and complexity of data analysis models, modern big data analytic applications face the challenge to provide timely results often with limited resources. Such demand drives the growth of new hardware resources including GPUs and FPGAs, as well as storage devices such as SSDs and NVMs. It is challenging to manage the resources available in a cost restricted environment to best serve the applications with different characteristics. Extant approaches are agnostic to such h
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Marques, Ricardo Jorge de Santiago. "Big data model with SQL support for performance management in telecommunication networks." Master's thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/14558.

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Mestrado em Sistemas de Informação<br>Com o tempo, a informação mantida pelas aplicações tem vindo a crescer e espera-se um crescimento exponencialmente na área de banda larga móvel com o surgimento da LTE. Com este crescimento cada vez maior de dados gerados, surge a necessidade de os manter por um período maior de tempo e as RDBMS não respondem rápido o suficiente. Isto fez com que as empresas se se tenham afastado das RDBMS e em busca de outras alternativas. As novas abordagens para o aumento do processamento de dados baseiam-se no desempenho, escalabilidade e robustez. O foco é semp
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Obeso, Duque Aleksandra. "Performance Prediction for Enabling Intelligent Resource Management on Big Data Processing Workflows." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-372178.

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Mobile cloud computing offers an augmented infrastructure that allows resource-constrained devices to use remote computational resources as an enabler for highly intensive computation, thus improving end users experience. Being able to efficiently manage cloud elasticity represents a big challenge for dynamic resource scaling on-demand. In this sense, the development of intelligent tools that could ease the understanding of the behavior of a highly dynamic system and to detect resource bottlenecks given certain service level constrains represents an interesting case of study. In this project,
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Formusa, Silvia <1996&gt. "China and Big Data management. Analysis from individuals' to foreign enterprises' perspective." Master's Degree Thesis, Università Ca' Foscari Venezia, 2020. http://hdl.handle.net/10579/18214.

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The aim of this writing is to provide a wider knowledge about Big Data management in China and to analyze the rigid dichotomy between their economic and political value. On the one hand, the State safeguards people’s information from the misuse of private actors through the consumers’ data protection law and assumes a central role among Asian countries for data privacy policy, insisting at the same time in maintaining some Chinese characteristics. On the other hand, the monitoring nature of the government as well as global scandals, increased the commitment of China to control both the cybersp
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OSMAN, NISRINE. "Big Data Management Towards Impact Assessment of Level 3 Automated Driving Functions." Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1051582.

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As industrial research in automated driving is rapidly advancing, it is of paramount importance to analyze field data from extensive road tests. This thesis presents a research work done in L3Pilot, the first comprehensive test of automated driving functions (ADFs) on public roads in Europe. L3Pilot is now completing the test of ADFs in vehicles by 13 companies. The tested functions are mainly of Society of Automotive Engineers (SAE) automation level 3, some of level 4. The overall collaboration among several organizations led to the design and development of a toolchain aimed at p
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Khalilikhah, Majid. "Traffic Sign Management: Data Integration and Analysis Methods for Mobile LiDAR and Digital Photolog Big Data." DigitalCommons@USU, 2016. https://digitalcommons.usu.edu/etd/4744.

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This study links traffic sign visibility and legibility to quantify the effects of damage or deterioration on sign retroreflective performance. In addition, this study proposes GIS-based data integration strategies to obtain and extract climate, location, and emission data for in-service traffic signs. The proposed data integration strategy can also be used to assess all transportation infrastructures’ physical condition. Additionally, non-parametric machine learning methods are applied to analyze the combined GIS, Mobile LiDAR imaging, and digital photolog big data. The results are presented
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Upadhyay, Abhyudaya. "Big Vector: An External Memory Algorithm and Data Structure." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439279714.

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Gogolou, Anna. "Iterative and Expressive Querying for Big Data Series." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS415.

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Les séries temporelles deviennent omniprésentes dans la vie moderne et leur analyse de plus en plus difficile compte tenu de leur taille. L’analyse des grandes séries de données implique des tâches telles que l’appariement de modèles (motifs), la détection d’anomalies, l’identification de modèles fréquents, et la classification ou le regroupement (clustering). Ces tâches reposent sur la notion de similarité. La communauté scientifique a proposé de plusieurs techniques, y compris de nombreuses mesures de similarité pour calculer la distance entre deux séries temporelles, ainsi que des technique
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Laterza, Marco. "Strategie di ingegnerizzazione e di sviluppo di sistemi software per big data management." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016.

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Il lavoro svolto si concentra sullo studio e lo sviluppo dei sistemi software per la gestione dei big data. Inizialmente sono stati analizzati i settori nei quali i big data si stanno diffondendo maggiormente per poi studiare l'ingegnerizzazione e lo sviluppo dei sistemi in grado di gestire questo tipo di dati. Sono state studiate tutte le fasi del processo di realizzazione del software e i rischi e i problemi che si possono incontrare. Infine è stato presentato un software di analisi di big data: Google BigQuery.
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Akpakpan, Nsikak Etim. "Analytic Extensions to the Data Model for Management Analytics and Decision Support in the Big Data Environment." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/5538.

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From 2006 to 2016, an estimated average of 50% of big data analytics and decision support projects failed to deliver acceptable and actionable outputs to business users. The resulting management inefficiency came with high cost, and wasted investments estimated at $2.7 trillion in 2016 for companies in the United States. The purpose of this quantitative descriptive study was to examine the data model of a typical data analytics project in a big data environment for opportunities to improve the information created for management problem-solving. The research questions focused on finding artifac
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Galarreta, Atoche Mayra Isabel, and Chafloque Israel Bryan Vélez. "La ética aplicada en el uso de la Big Data." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2020. http://hdl.handle.net/10757/653432.

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La presente investigación se centra en exponer las diversas opiniones desarrolladas en torno a la ética y el uso de la Big Data, es decir, los macrodatos. Para ello, se ha realizado una indagación sistemática de fuentes publicadas en un marco temporal comprendido entre los años 2015-2020 con la intención de recuperar los acercamientos más recientes que se han centrado en la relación de estas dos variables. Se han planteado, principalmente, cuatro objetivos que organizan la estructura del trabajo. En un primer momento, se busca establecer un alcance de lo que se entiende por ética y cómo esta s
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Xu, Yiqi. "Storage Management of Data-intensive Computing Systems." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2474.

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Computing systems are becoming increasingly data-intensive because of the explosion of data and the needs for processing the data, and storage management is critical to application performance in such data-intensive computing systems. However, existing resource management frameworks in these systems lack the support for storage management, which causes unpredictable performance degradations when applications are under I/O contention. Storage management of data-intensive systems is a challenging problem because I/O resources cannot be easily partitioned and distributed storage systems require s
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Saenyi, Betty. "Opportunities and challenges of Big Data Analytics in healthcare : An exploratory study on the adoption of big data analytics in the Management of Sickle Cell Anaemia." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Informatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-42864.

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Background: With increasing technological advancements, healthcare providers are adopting electronic health records (EHRs) and new health information technology systems. Consequently, data from these systems is accumulating at a faster rate creating a need for more robust ways of capturing, storing and processing the data. Big data analytics is used in extracting insight form such large amounts of medical data and is increasingly becoming a valuable practice for healthcare organisations. Could these strategies be applied in disease management? Especially in rare conditions like Sickle Cell Dis
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Jayapandian, Catherine Praveena. "Cloudwave: A Cloud Computing Framework for Multimodal Electrophysiological Big Data." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1405516626.

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Martinelli, Paride. "Big-data e Turismo: Analisi delle recensioni utente sulla piattaforma Expedia." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10372/.

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Big data e turismo è il tema principale di questa tesi: esamina l'utilizzo dei social media come mezzo di interazione tra turisti e albergatori, prendendo come riferimento la piattaforma di booking Expedia.com e come campione di hotel tutti gli hotel della penisola italiana. In particolare si vogliono studiare i due tipi di utenti che utilizzano questo tipo di piatta forma, ovvero turisti e albergatori. Dei turisti si vuole capire il loro livello di attività su social media, calcolando l'andamento delle recensioni postate; poi si passa ad uno studio della singola recensione e infine si è cerc
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Martins, Pedro Miguel Pereira Serrano. "Evaluation and optimization of a session-based middleware for data management." Master's thesis, Faculdade de Ciências e Tecnologia, 2014. http://hdl.handle.net/10362/12609.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática<br>The current massive daily production of data has created a non-precedent opportunity for information extraction in many domains. However, this huge rise in the quantities of generated data that needs to be processed, stored, and timely delivered, has created several new challenges. In an effort to attack these challenges [Dom13] proposed a middleware with the concept of a Session capable of dynamically aggregating, processing and disseminating large amounts of data to groups of clients, depending on their interests.
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Nybacka, A. (Aino). "Privacy concerns of consumers in big data management for marketing purposes:an integrative literature review." Bachelor's thesis, University of Oulu, 2016. http://urn.fi/URN:NBN:fi:oulu-201605261989.

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This bachelor’s thesis is a literature review about big data, privacy concerns for individual consumers and how these two overlap together in a way to possibly explain what are the privacy concerns that customers have, and the companies maybe should think about, when they utilize data as a marketing tool. The thesis introduces an integrative framework for the privacy concerns emerging from the process of big data management for marketing purposes and gives insights for phases in this process first separately from companies point of view, then from the consumers point of view regarding the pri
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Jain, Sheenam. "Big data management using artificial intelligence in the apparel supply chain : opportunities and challenges." Thesis, Lille 1, 2020. http://www.theses.fr/2020LIL1I051.

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L’industrie de l'habillement a bénéficié, au cours de la dernière décennie, de l'application de big data et de l'intelligence artificielle pour résoudre divers problèmes commerciaux. Face à la concurrence accrue sur le marché et aux attentes des clients en matière de personnalisation, ces industriels sont en permanence à la recherche des moyens d'améliorer leurs stratégies commerciales afin d'accroître leur rapidité et leur rentabilité. A cet égard, les solutions de gestion de big data offrent aux enseignes de la distribution textile la possibilité d'explorer leur chaîne d'approvisionnement et
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Ephraim, Ekow Esson, and Sanel Sehic. "The Use of Big Data in Process Management : A Literature Study and Survey Investigation." Thesis, Linköpings universitet, Logistik- och kvalitetsutveckling, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177921.

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In recent years there has been an increasing interest in understanding how organizations can utilize big data in their process management to create value and improve their processes. This is due to new challenges for process management which have arisen from increasing competition and the complexity of large data sets due to technological advancements. These large data sets have been described by scholars as big data which involves data that are so complex traditional data analysis software are not sufficient in managing or analyzing them. Because of the complexity of handling such great volum
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Halwani, Marwah Ahmed. "The Evolution of Big Data and Its Business Applications." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1157644/.

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The arrival of the Big Data era has become a major topic of discussion in many sectors because of the premises of big data utilizations and its impact on decision-making. It is an interdisciplinary issue that has captured the attention of scholars and created new research opportunities in information science, business, heath care, and many others fields. The problem is the Big Data is not well defined, so that there exists confusion in IT what jobs and skill sets are required in big data area. The problem stems from the newness of the Big Data profession. Because many aspects of the area are
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Venturi, Bartolini Silvia. "Big-data e turismo Estrazione ed analisi dei dati dalla piattaforma Expedia." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/11907/.

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Vitale, Giovanni. "big data e data warehouse per supporto alle decisioni in ambito aziendale: un caso di studio." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22948/.

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La mia tesi tratta di un caso di studio dell'utilizzo dei big data nell'infrastruttura data warehouse e della teoria ad esso legata. Il progetto è stato svolto durante il tirocinio in azienda (Iconsulting S.p.A.) e l'obiettivo finale è stato l'esecuzione di un'importante migrazione tecnologica di una dashboard per un cliente del settore Manufacturing. Per migrazione tecnologica si intende copiare tabelle e viste, legate alla dashboard per cui è richiesto il progetto, da database di origine di una tecnologia (in questo caso Netezza) a database di destinazione (in questo caso Hana), convertendo
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DJURSÉN, WILLIAM, and JOHN SÖDERBERG. "Projektplaneringens hantering av big data : En studie av företag som utvecklar medicinteknsika produkter." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279781.

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En ökad användning av teknologi inom det medicinska fältet har öppnat möjligheter att använda patientdata i nya medicintekniska produkter. Genom användningen av sensorer och appar har det skapats en stor mängd patientdata. I detta sammanhang har begreppet big data inträffat. Dock finns det ingen tydlig definition för att beskriva big data eftersom det inte finns någon gräns för mycket data som krävs för termen. Syftet med denna undersökning är att granska om och i så fall hur medicinsktekniska företag anpassar sin projektplanering med hänsyn till möjlig användning av big data. Målet är också a
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Mercier, Michael. "Contribution to High Performance Computing and Big Data Infrastructure Convergence." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAM031/document.

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La quantité de données produites dans le monde scientifique comme dans le monde commercial, est en constante augmentation. Le domaine du traitement de donnée à large échelle, appelé “Big Data”, a été inventé pour traiter des données sur de larges infrastructures informatiques distribuées. Mais l’intégration de système Big Data sur des machines de calcul intensif pose de nombreux problèmes. En effet, les gestionnaires de ressources ainsi que les systèmes de fichier de super calculateurs ne sont pas penser pour ce type de travail. Le sujet de cette thèse est de trouver la meilleure approche pour
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