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Tesis sobre el tema "Data"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 25 de julio de 2025

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1

Riminucci, Stefania. "COVID-19,Open data e data visualization:interazione con dati epidemiologici." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21577/.

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L’obiettivo di questa tesi è quello di analizzare l’efficacia di diverse strategie di data visualization utilizzate per presentare open data in forma grafica alla popolazione. Come caso di studio, si è presa in considerazione la pandemia di COVID-19, e le molteplici visualizzazioni che sfruttano gli open data messi a disposizione dalle comunità scientifiche, offrendo informazioni sull'evoluzione dei contagi a livello nazionale e internazionale. Per valutare l’efficacia delle diverse visualizzazioni, è stato sviluppato e proposto al pubblico un questionario per la raccolta di dati per ave
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2

Mondaini, Luca. "Data Visualization di dati spazio-temporali." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/16853/.

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Questa tesi propone, dopo aver introdotto le tipologie di dato esistenti e i concetti di Big Data, Open Data e Data Visualization, due obiettivi differenti: ottenere informazioni utilizzando le API di Google Maps, più precisamente, latitudine e longitudine di ogni indirizzo di domicilio degli studenti immatricolati in UniBo e la visualizzazione di questi dati, all'interno di un'applicazione web, mediante istogrammi e mappe digitali interattivi con l'utilizzo di tecniche di Data Visualization.
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3

Yu, Wenyuan. "Improving data quality : data consistency, deduplication, currency and accuracy." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/8899.

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Data quality is one of the key problems in data management. An unprecedented amount of data has been accumulated and has become a valuable asset of an organization. The value of the data relies greatly on its quality. However, data is often dirty in real life. It may be inconsistent, duplicated, stale, inaccurate or incomplete, which can reduce its usability and increase the cost of businesses. Consequently the need for improving data quality arises, which comprises of five central issues of improving data quality, namely, data consistency, data deduplication, data currency, data accuracy and
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4

Long, Christopher C. "Data Processing for NASA's TDRSS DAMA Channel." International Foundation for Telemetering, 1996. http://hdl.handle.net/10150/611474.

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International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California<br>Presently, NASA's Space Network (SN) does not have the ability to receive random messages from satellites using the system. Scheduling of the service must be done by the owner of the spacecraft through Goddard Space Flight Center (GSFC). The goal of NASA is to improve the current system so that random messages, that are generated on board the satellite, can be received by the SN. The messages will be requests for service that the satellites control sy
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5

Budd, Chris. "Data Protection and Data Elimination." International Foundation for Telemetering, 2015. http://hdl.handle.net/10150/596395.

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ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV<br>Data security is becoming increasingly important in all areas of storage. The news services frequently have stories about lost or stolen storage devices and the panic it causes. Data security in an SSD usually involves two components: data protection and data elimination. Data protection includes passwords to protect against unauthorized access and encryption to protect against recovering data fro
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6

Furrier, Sean Alexander, and Sean Alexander Furrier. "Communicating Data: Data-Driven Storytelling." Thesis, The University of Arizona, 2017. http://hdl.handle.net/10150/624989.

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Data is more abundant than ever, yet its utility is diminished by a lack of understanding and difficulty in communicating insights. This thesis seeks to test the effectiveness of data-driven storytelling as a means to solve this disconnect. Research conducted includes reading previous literature on the subject, interviewing journalists and data practitioners as well as learning to use various software tools. This research focuses on communicating engaging stories by finding, cleaning, analyzing and visualizing data using R, Python, Excel, Tableau, Carto and other software tools. The res
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7

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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BRASCHI, GIACOMO. "La circolazione dei dati e l'analisi big data." Doctoral thesis, Università degli studi di Pavia, 2019. http://hdl.handle.net/11571/1244327.

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Descrizione degli strumenti giuridici che regolano la circolazione dei dati e analisi dei possibili sviluppi normativi auspicabile per favori la circolazione dei dati<br>Description of the legal instruments that regulate the circulation of data and analysis of possible legislative developments desirable to favor the circulation of data
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9

Perovich, Laura J. (Laura Jones). "Data Experiences : novel interfaces for data engagement using environmental health data." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/95612.

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Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 71-81).<br>For the past twenty years, the data visualization movement has reworked the way we engage with information. It has brought fresh excitement to researchers and reached broad audiences. But what comes next for data? I seek to create example "Data Experiences" that will contribute to developing new spaces of information engagement. Using data from Silent Spring Institute
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10

Wang, Yi. "Data Management and Data Processing Support on Array-Based Scientific Data." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1436157356.

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11

Dedge, Parks Dana M. "Defining Data Science and Data Scientist." Thesis, University of South Florida, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10639701.

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<p> The world&rsquo;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 capab
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12

Proskurnia, Iuliia. "Genium Data Store : Distributed Data store." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-141552.

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In recent years the need for distributed data storage has led the way to design new systems in a large-scale environment. The growth of unbounded stream of data, the necessity to store and analyze it in real time, reliably, scalable and fast are the reasons for appearance of such systems in financial sector, stock exchange Nasdaq OMX especially. Furthermore, internally designed totally ordered reliable message bus is used in Nasdaq OMX for almost all internal subsystems. Theoretical and practical extensive studies on reliable totally ordered multicast were made in academia and it was proven to
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13

Morshedzadeh, Iman. "Data Classification in Product Data Management." Thesis, Högskolan i Skövde, Institutionen för teknik och samhälle, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-14651.

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This report is about the product data classification methodology that is useable for the Volvo Cars Engine (VCE) factory's production data, and can be implemented in the Teamcenter software. There are many data generated during the life cycle of each product, and companies try to manage these data with some product data management software. Data classification is a part of data management for most effective and efficient use of data. With surveys that were done in this project, items affecting the data classification have been found. Data, attributes, classification method, Volvo Cars Engine f
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14

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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15

Strand, Mattias. "External Data Incorporation into Data Warehouses." Doctoral thesis, Kista : Skövde : Dept. of computer and system sciences, Stockholm University : School of humanities and informatics, University of Skövde, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-660.

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Radhakrishnan, Radhika. "Genome data modeling and data compression." abstract and full text PDF (free order & download UNR users only), 2007. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1447611.

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17

Abedjan, Ziawasch. "Improving RDF data with data mining." Phd thesis, Universität Potsdam, 2014. http://opus.kobv.de/ubp/volltexte/2014/7133/.

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Linked Open Data (LOD) comprises very many and often large public data sets and knowledge bases. Those datasets are mostly presented in the RDF triple structure of subject, predicate, and object, where each triple represents a statement or fact. Unfortunately, the heterogeneity of available open data requires significant integration steps before it can be used in applications. Meta information, such as ontological definitions and exact range definitions of predicates, are desirable and ideally provided by an ontology. However in the context of LOD, ontologies are often incomplete or simply not
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18

Fahmy, A. "Data encryption of communication data links." Thesis, University of Kent, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385199.

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19

Sun, Wenjun. "Parallel data processing for semistructured data." Thesis, London South Bank University, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.434394.

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20

Wiemann, Stefan. "Data Fusion in Spatial Data Infrastructures." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-216985.

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Over the past decade, the public awareness and availability as well as methods for the creation and use of spatial data on the Web have steadily increased. Besides the establishment of governmental Spatial Data Infrastructures (SDIs), numerous volunteered and commercial initiatives had a major impact on that development. Nevertheless, data isolation still poses a major challenge. Whereas the majority of approaches focuses on data provision, means to dynamically link and combine spatial data from distributed, often heterogeneous data sources in an ad hoc manner are still very limited. However,
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21

Virinchi, Billa. "Data Visualization of Telenor mobility data." Thesis, Blekinge Tekniska Högskola, Institutionen för kommunikationssystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13951.

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Nowadays with the rapid development of cities, understanding the human mobility patterns of subscribers is crucial for urban planning and for network infrastructure deployment. Today mobile phones are electronic devices used for analyzing the mobility patterns of the subscribers in the network, because humans in their daily activities they carry mobile phones for communication purpose. For effective utilization of network infrastructure (NI) there is a need to study on mobility patterns of subscribers.   The aim of the thesis is to simulate the geospatial Telenor mobility data (i.e. three diff
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22

Gullipalli, Deep Kumar. "Data envelopment analysis with sparse data." Thesis, Kansas State University, 2011. http://hdl.handle.net/2097/13092.

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Master of Science<br>Department of Industrial & Manufacturing Systems Engineering<br>David H. Ben-Arieh<br>Quest for continuous improvement among the organizations and issue of missing data for data analysis are never ending. This thesis brings these two topics under one roof, i.e., to evaluate the productivity of organizations with sparse data. This study focuses on Data Envelopment Analysis (DEA) to determine the efficiency of 41 member clinics of Kansas Association of Medically Underserved (KAMU) with missing data. The primary focus of this thesis is to develop new reliable methods to deter
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23

Kostopoulos, A. "Combinatorial data analysis for data ordering." Thesis, University of Liverpool, 2016. http://livrepository.liverpool.ac.uk/3004631/.

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Seriation is a combinatorial optimisation problem that aims to sequence a set of objects such that a natural ordering is created. A large variety of applications exist ranging from archaeology to bioinformatics and text mining. Initially, a thorough and useful quantitative analysis compares different seriation algorithms using the positional proximity coefficient (PPC). This analysis helps the practitioner to understand how similar two algorithms are for a given set of datasets. The first contribution is consensus seriation. This method uses the principles of other consensus based methods to c
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24

Tata, Maitreyi. "Data analytics on Yelp data set." Kansas State University, 2017. http://hdl.handle.net/2097/38237.

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Master of Science<br>Department of Computing and Information Sciences<br>William H. Hsu<br>In this report, I describe a query-driven system which helps in deciding which restaurant to invest in or which area is good to open a new restaurant in a specific place. Analysis is performed on already existing businesses in every state. This is based on certain factors such as the average star rating, the total number of reviews associated with a specific restaurant, the price range of the restaurant etc. The results will give an idea of successful restaurants in a city, which helps you decide where
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25

Liu, Tantan. "Data Mining over Hidden Data Sources." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1343313341.

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26

Yang, Ying. "Interactive Data Management and Data Analysis." Thesis, State University of New York at Buffalo, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10288109.

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<p> Everyone today has a big data problem. Data is everywhere and in different formats, they can be referred to as data lakes, data streams, or data swamps. To extract knowledge or insights from the data or to support decision-making, we need to go through a process of collecting, cleaning, managing and analyzing the data. In this process, data cleaning and data analysis are two of the most important and time-consuming components. </p><p> One common challenge in these two components is a lack of interaction. The data cleaning and data analysis are typically done as a batch process, operati
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27

Taylor, Phillip. "Data mining of vehicle telemetry data." Thesis, University of Warwick, 2015. http://wrap.warwick.ac.uk/77645/.

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Driving a safety critical task that requires a high level of attention and workload from the driver. Despite this, people often perform secondary tasks such as eating or using a mobile phone, which increase workload levels and divert cognitive and physical attention from the primary task of driving. As well as these distractions, the driver may also be overloaded for other reasons, such as dealing with an incident on the road or holding conversations in the car. One solution to this distraction problem is to limit the functionality of in-car devices while the driver is overloaded. This can tak
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28

Yao, Fang. "Functional data analysis for longitudinal data /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2003. http://uclibs.org/PID/11984.

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Ramljak, Dusan. "Data Driven High Performance Data Access." Diss., Temple University Libraries, 2018. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/530207.

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Computer and Information Science<br>Ph.D.<br>Low-latency, high throughput mechanisms to retrieve data become increasingly crucial as the cyber and cyber-physical systems pour out increasing amounts of data that often must be analyzed in an online manner. Generally, as the data volume increases, the marginal utility of an ``average'' data item tends to decline, which requires greater effort in identifying the most valuable data items and making them available with minimal overhead. We believe that data analytics driven mechanisms have a big role to play in solving this needle-in-the-haystack pr
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30

Sherikar, Vishnu Vardhan Reddy. "I2MAPREDUCE: DATA MINING FOR BIG DATA." CSUSB ScholarWorks, 2017. https://scholarworks.lib.csusb.edu/etd/437.

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This project is an extension of i2MapReduce: Incremental MapReduce for Mining Evolving Big Data . i2MapReduce is used for incremental big data processing, which uses a fine-grained incremental engine, a general purpose iterative model that includes iteration algorithms such as PageRank, Fuzzy-C-Means(FCM), Generalized Iterated Matrix-Vector Multiplication(GIM-V), Single Source Shortest Path(SSSP). The main purpose of this project is to reduce input/output overhead, to avoid incurring the cost of re-computation and avoid stale data mining results. Finally, the performance of i2MapReduce is anal
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31

Mathew, Avin D. "Asset management data warehouse data modelling." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/19310/1/Avin_Mathew_Thesis.pdf.

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Data are the lifeblood of an organisation, being employed by virtually all business functions within a firm. Data management, therefore, is a critical process in prolonging the life of a company and determining the success of each of an organisation’s business functions. The last decade and a half has seen data warehousing rising in priority within corporate data management as it provides an effective supporting platform for decision support tools. A cross-sectional survey conducted by this research showed that data warehousing is starting to be used within organisations for their engineering
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32

Mathew, Avin D. "Asset management data warehouse data modelling." Queensland University of Technology, 2008. http://eprints.qut.edu.au/19310/.

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Data are the lifeblood of an organisation, being employed by virtually all business functions within a firm. Data management, therefore, is a critical process in prolonging the life of a company and determining the success of each of an organisation’s business functions. The last decade and a half has seen data warehousing rising in priority within corporate data management as it provides an effective supporting platform for decision support tools. A cross-sectional survey conducted by this research showed that data warehousing is starting to be used within organisations for their engineering
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33

Niggemann, Oliver. "Visual data mining of graph based data." [S.l. : s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=962400505.

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34

Peralta, Veronika. "Data Quality Evaluation in Data Integration Systems." Phd thesis, Université de Versailles-Saint Quentin en Yvelines, 2006. http://tel.archives-ouvertes.fr/tel-00325139.

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Les besoins d'accéder, de façon uniforme, à des sources de données multiples, sont chaque jour plus forts, particulièrement, dans les systèmes décisionnels qui ont besoin d'une analyse compréhensive des données. Avec le développement des Systèmes d'Intégration de Données (SID), la qualité de l'information est devenue une propriété de premier niveau de plus en plus exigée par les utilisateurs. Cette thèse porte sur la qualité des données dans les SID. Nous nous intéressons, plus précisément, aux problèmes de l'évaluation de la qualité des données délivrées aux utilisateurs en réponse à leurs re
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35

Sánchez, Adam. "Big Data, Linked Data y Web semántica." Universidad Peruana de Ciencias Aplicadas (UPC), 2016. http://hdl.handle.net/10757/620705.

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Conferencia realizada en el marco de la Semana del Acceso Abierto Perú, llevada a cabo del 24 al 26 de Octubre de 2016 en Lima, Peru. Las instituciones organizadoras: Universidad Peruana de Ciencias aplciadasd (UPC), Pontificia Universidad Católica del Perú (PUCP) y Universidad Peruana Cayetano Heredia (UPCH).<br>Conferencia que aborda aspectos del protocolo Linked Data, temas de Big Data y Web Semantica,
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36

Nyström, Simon, and Joakim Lönnegren. "Processing data sources with big data frameworks." Thesis, KTH, Data- och elektroteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188204.

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Big data is a concept that is expanding rapidly. As more and more data is generatedand garnered, there is an increasing need for efficient solutions that can be utilized to process all this data in attempts to gain value from it. The purpose of this thesis is to find an efficient way to quickly process a large number of relatively small files. More specifically, the purpose is to test two frameworks that can be used for processing big data. The frameworks that are tested against each other are Apache NiFi and Apache Storm. A method is devised in order to, firstly, construct a data flow and sec
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37

Li, Liangchun. "Web-based data visualization for data mining." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ35845.pdf.

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38

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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Zebbiche, K. "Data Hiding for Securing Fingerprint Data Access." Thesis, Queen's University Belfast, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.517622.

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40

Jägerhult, Fjelberg Marianne. "Predicting data traffic in cellular data networks." Thesis, KTH, Matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169388.

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The exponential increase in cellular data usage in recent time is evident, which introduces challenges and opportunities for the telecom industry. From a Radio Resource Management perspective, it is therefore most valuable to be able to predict future events such as user load. The objective of this thesis is thus to investigate whether one can predict such future events based on information available in a base station. This is done by clustering data obtained from a simulated 4G network using Gaussian Mixture Models. Based on this, an evaluation based on the cluster signatures is performed, wh
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41

Ross, Colin. "Applications of data fusion in data approximation." Thesis, University of Huddersfield, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.247372.

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42

Conlin, Adrian Keith. "Complex sensor data analysis through data augmentation." Thesis, University of Newcastle Upon Tyne, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320016.

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43

Cao, Yang. "Querying big data with bounded data access." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/25421.

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Query answering over big data is cost-prohibitive. A linear scan of a dataset D may take days with a solid state device if D is of PB size and years if D is of EB size. In other words, polynomial-time (PTIME) algorithms for query evaluation are already not feasible on big data. To tackle this, we propose querying big data with bounded data access, such that the cost of query evaluation is independent of the scale of D. First of all, we propose a class of boundedly evaluable queries. A query Q is boundedly evaluable under a set A of access constraints if for any dataset D that satisfies constra
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44

Mueller, G. "Data Consistency Checks on Flight Test Data." International Foundation for Telemetering, 2014. http://hdl.handle.net/10150/577405.

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ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA<br>This paper reflects the principal results of a study performed internally by Airbus's flight test centers. The purpose of this study was to share the body of knowledge concerning data consistency checks between all Airbus business units. An analysis of the test process is followed by the identification of the process stakeholders involved in ensuring data consistency. In the main part of th
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45

Fitzgerald, Alan. "DATA STORAGE SUITED TO FLIGHT DATA RECORDERS." International Foundation for Telemetering, 2004. http://hdl.handle.net/10150/605266.

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46

Oladele, Kazeem Ayinde. "Investigating pluralistic data architectures in data warehousing." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/10534.

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Understanding and managing change is a strategic objective for many organisations to successfully compete in a market place; as a result, organisations are leveraging their data asset and implementing data warehouses to gain business intelligence necessary to improve their businesses. Data warehouses are expensive initiatives, one-half to two-thirds of most data warehousing efforts end in failure. In the absence of well-formalised design methodology in the industry and in the context of the debate on data architecture in data warehousing, this thesis examines why multidimensional and relationa
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47

Peralta, Costabel Veronika del Carmen. "Data quality evaluation in data integration systems." Versailles-St Quentin en Yvelines, 2006. http://www.theses.fr/2006VERS0020.

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This thesis deals with data quality evaluation in Data Integration Systems (DIS). Specifically, we address the problems of evaluating the quality of the data conveyed to users in response to their queries and verifying if users’ quality expectations can be achieved. We also analyze how quality measures can be used for improving the DIS and enforcing data quality. Our approach consists in studying one quality factor at a time, analyzing its impact within a DIS, proposing techniques for its evaluation and proposing improvement actions for its enforcement. Among the quality factors that have been
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48

Zhang, Yihua. "ON DATA UTILITY IN PRIVATE DATA PUBLISHING." Miami University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=miami1272986770.

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49

Modur, Sharada P. "Missing Data Methods for Clustered Longitudinal Data." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1274876785.

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Zha, Xiao. "Topological Data Analysis on Road Network Data." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu155563664988436.

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