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Dissertations / Theses on the topic 'Data and Data Quality'

Author: Grafiati
Published: 10 September 2021
Last updated: 29 July 2025

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1

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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2

Grillo, Aderibigbe. "Developing a data quality scorecard that measures data quality in a data warehouse." Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/17137.

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The main purpose of this thesis is to develop a data quality scorecard (DQS) that aligns the data quality needs of the Data warehouse stakeholder group with selected data quality dimensions. To comprehend the research domain, a general and systematic literature review (SLR) was carried out, after which the research scope was established. Using Design Science Research (DSR) as the methodology to structure the research, three iterations were carried out to achieve the research aim highlighted in this thesis. In the first iteration, as DSR was used as a paradigm, the artefact was build from the r
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3

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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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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5

Deb, Rupam. "Data Quality Enhancement for Traffic Accident Data." Thesis, Griffith University, 2017. http://hdl.handle.net/10072/367725.

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Death, injury, and disability resulting from road traffic crashes continue to be a major global public health problem. Recent data suggest that the number of fatalities from traffic crashes is in excess of 1.25 million people each year with non-fatal injuries affecting a further 20-50 million people. It is predicted that by 2030, road traffic accidents will have progressed to be the 5th leading cause of death and that the number of people who will die annually from traffic accidents will have doubled from current levels. Both developed and developing countries suffer from the consequences of t
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Sýkorová, Veronika. "Data Quality Metrics." Master's thesis, Vysoká škola ekonomická v Praze, 2008. http://www.nusl.cz/ntk/nusl-2815.

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The aim of the thesis is to prove measurability of the Data Quality which is a relatively subjective measure and thus is difficult to measure. In doing this various aspects of measuring the quality of data are analyzed and a Complex Data Quality Monitoring System is introduced with the aim to provide a concept for measuring/monitoring the overall Data Quality in an organization. The system is built on a metrics hierarchy decomposed into particular detailed metrics, dimensions enabling multidimensional analyses of the metrics, and processes being measured by the metrics. The first part of the t
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7

Redgert, Rebecca. "Evaluating Data Quality in a Data Warehouse Environment." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208766.

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The amount of data accumulated by organizations have grown significantly during the last couple of years, increasing the importance of data quality. Ensuring data quality for large amounts of data is a complicated task, but crucial to subsequent analysis. This study investigates how to maintain and improve data quality in a data warehouse. A case study of the errors in a data warehouse was conducted at the Swedish company Kaplan, and resulted in guiding principles on how to improve the data quality. The investigation was done by manually comparing data from the source systems to the data integ
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8

Bringle, Per. "Data Quality in Data Warehouses: a Case Study." Thesis, University of Skövde, Department of Computer Science, 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-404.

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<p>Companies today experience problems with poor data quality in their systems. Because of the enormous amount of data in companies, the data has to be of good quality if companies want to take advantage of it. Since the purpose with a data warehouse is to gather information from several databases for decision support, it is absolutely vital that data is of good quality. There exists several ways of determining or classifying data quality in databases. In this work the data quality management in a large Swedish company's data warehouse is examined, through a case study, using a framework speci
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9

Li, Lin. "Data quality and data cleaning in database applications." Thesis, Edinburgh Napier University, 2012. http://researchrepository.napier.ac.uk/Output/5788.

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Today, data plays an important role in people's daily activities. With the help of some database applications such as decision support systems and customer relationship management systems (CRM), useful information or knowledge could be derived from large quantities of data. However, investigations show that many such applications fail to work successfully. There are many reasons to cause the failure, such as poor system infrastructure design or query performance. But nothing is more certain to yield failure than lack of concern for the issue of data quality. High quality of data is a key to to
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10

He, Ying Surveying &amp Spatial Information Systems Faculty of Engineering UNSW. "Spatial data quality management." Publisher:University of New South Wales. Surveying & Spatial Information Systems, 2008. http://handle.unsw.edu.au/1959.4/43323.

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The applications of geographic information systems (GIS) in various areas have highlighted the importance of data quality. Data quality research has been given a priority by GIS academics for three decades. However, the outcomes of data quality research have not been sufficiently translated into practical applications. Users still need a GIS capable of storing, managing and manipulating data quality information. To fill this gap, this research aims to investigate how we can develop a tool that effectively and efficiently manages data quality information to aid data users to better understand a
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11

Barker, James M. "Data governance| The missing approach to improving data quality." Thesis, University of Phoenix, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10248424.

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<p> In an environment where individuals use applications to drive activities from what book to purchase, what film to view, to what temperature to heat a home, data is the critical element. To make things work data must be correct, complete, and accurate. Many firms view data governance as a panacea to the ills of systems and organizational challenge while other firms struggle to generate the value of these programs. This paper documents a study that was executed to understand what is being done by firms in the data governance space and why? The conceptual framework that was established from t
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12

Wolf, Hilke. "Data Quality Bench-Marking for High Resolution Bragg Data." Doctoral thesis, Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2014. http://hdl.handle.net/11858/00-1735-0000-0022-5DE2-A.

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13

Swapna, B., and R. VijayaPrakash. "Privacy Preserving Data Mining Operations without Disrupting Data Quality." International Journal of Computer Science and Network (IJCSN), 2012. http://hdl.handle.net/10150/271473.

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Data mining operations have become prevalent as they can extract trends or patterns that help in taking good business decisions. Often they operate on large historical databases or data warehouses to obtain actionable knowledge or business intelligence that helps in taking well informed decisions. In the data mining domain there came many tools to perform data mining operations. These tools are best used to obtain actionable knowledge from data. Manually doing this is not possible as the data is very huge and takes lot of time. Thus the data mining domain is being improved in a rapid
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14

Landelius, Cecilia. "Data governance in big data : How to improve data quality in a decentralized organization." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301258.

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The use of internet has increased the amount of data available and gathered. Companies are investing in big data analytics to gain insights from this data. However, the value of the analysis and decisions made based on it, is dependent on the quality ofthe underlying data. For this reason, data quality has become a prevalent issue for organizations. Additionally, failures in data quality management are often due to organizational aspects. Due to the growing popularity of decentralized organizational structures, there is a need to understand how a decentralized organization can improve data qua
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15

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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16

Angeles, Maria del Pilar. "Management of data quality when integrating data with known provenance." Thesis, Heriot-Watt University, 2007. http://hdl.handle.net/10399/64.

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17

Diallo, Thierno Mahamoudou. "Discovering data quality rules in a master data management context." Thesis, Lyon, INSA, 2013. http://www.theses.fr/2013ISAL0067.

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Le manque de qualité des données continue d'avoir un impact considérable pour les entreprises. Ces problèmes, aggravés par la quantité de plus en plus croissante de données échangées, entrainent entre autres un surcoût financier et un rallongement des délais. De ce fait, trouver des techniques efficaces de correction des données est un sujet de plus en plus pertinent pour la communauté scientifique des bases de données. Par exemple, certaines classes de contraintes comme les Dépendances Fonctionnelles Conditionnelles (DFCs) ont été récemment introduites pour le nettoyage de données. Les méthod
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18

Sehat, Mahdis, and FLORES RENÉ PAVEZ. "Customer Data Management." Thesis, KTH, Industriell ekonomi och organisation (Avd.), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-109251.

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Abstract As the business complexity, number of customers continues to grow and customers evolve into multinational organisations that operate across borders, many companies are faced with great challenges in the way they manage their customer data. In today’s business, a single customer may have a relationship with several entities of an organisation, which means that the customer data is collected through different channels. One customer may be described in different ways by each entity, which makes it difficult to obtain a unified view of the customer. In companies where there are several so
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SPAHIU, BLERINA. "Profiling Linked Data." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2017. http://hdl.handle.net/10281/151645.

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Nonostante l'elevato numero di dati pubblicati come LD, il loro utilizzo non ha ancora mostrato il loro potenziale per l’assenza di comprensione dei metadati. I consumatori di dati hanno bisogno di ottenere informazioni dai dataset in modo veloce e concentrato per poter decidere se sono utili per il loro problema oppure no. Le tecniche di profilazione dei dati offrono una soluzione efficace a questo problema in quanto sono utilizzati per generare metadati e statistiche che descrivono il contenuto dei dataset. Questa tesi presenta una ricerca, che affronta i problemi legati alla profilazione
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20

Wad, Charudatta V. "QoS : quality driven data abstraction for large databases." Worcester, Mass. : Worcester Polytechnic Institute, 2008. http://www.wpi.edu/Pubs/ETD/Available/etd-020508-151213/.

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21

Ma, Shuai. "Extending dependencies for improving data quality." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5045.

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This doctoral thesis presents the results of my work on extending dependencies for improving data quality, both in a centralized environment with a single database and in a data exchange and integration environment with multiple databases. The first part of the thesis proposes five classes of data dependencies, referred to as CINDs, eCFDs, CFDcs, CFDps and CINDps, to capture data inconsistencies commonly found in practice in a centralized environment. For each class of these dependencies, we investigate two central problems: the satisfiability problem and the implication problem. The satisfiab
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22

Dill, Robert W. "Data warehousing and data quality for a Spatial Decision Support System." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1997. http://handle.dtic.mil/100.2/ADA336886.

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Thesis (M.S. in Information Technology Management) Naval Postgraduate School, Sept. 1997.<br>Thesis advisors, Daniel R. Dolk, George W. Thomas, and Kathryn Kocher. Includes bibliographical references (p. 203-206). Also available online.
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23

Reinert, Olof, and Tobias Wiesinger. "DATA QUALITY CONSEQUENCES OF MANDATORY CYBER DATA SHARING BETWEEN DUOPOLY INSURERS." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-175180.

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Cyber attacks against companies are becoming more common as technology advances and digitalization is increasing exponentially. All Swedish insurance companies that sell cyber insurance encounter the same problem, there is not enough data to do good actuarial work. In order for the pricing procedure to improve and general knowledge of cyber insurance to increase, it has been proposed that insurance companies should share their data with each other. The goal of the thesis is to do mathematical calculations to explore data quality consequences of such a sharing regime. This thesis is based on so
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Alkharboush, Nawaf Abdullah H. "A data mining approach to improve the automated quality of data." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/65641/1/Nawaf%20Abdullah%20H_Alkharboush_Thesis.pdf.

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This thesis describes the development of a robust and novel prototype to address the data quality problems that relate to the dimension of outlier data. It thoroughly investigates the associated problems with regards to detecting, assessing and determining the severity of the problem of outlier data; and proposes granule-mining based alternative techniques to significantly improve the effectiveness of mining and assessing outlier data.
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Blahová, Leontýna. "Big Data Governance." Master's thesis, Vysoká škola ekonomická v Praze, 2016. http://www.nusl.cz/ntk/nusl-203994.

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This master thesis is about Big Data Governance and about software, which is used for this purposes. Because Big Data are huge opportunity and also risk, I wanted to map products which can be easily use for Data Quality and Big Data Governance in one platform. This thesis is not only on theoretical knowledge level, but also evaluates five key products (from my point of view). I defined requirements for every kind of domain and then I set up the weights and points. The main objective is to evaluate software capabilities and compere them.
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Gens, Rüdiger. "Quality assessment of SAR interferometric data." Hannover : Fachrichtung Vermessungswesen der Univ, 1998. http://deposit.ddb.de/cgi-bin/dokserv?idn=95607121X.

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Berg, Marcus. "Evaluating Quality of Online Behavior Data." Thesis, Stockholms universitet, Statistiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-97524.

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This thesis has two purposes; emphasizing the importance of data quality of Big Data, and identifying and evaluating potential error sources in JavaScript tracking (a client side on - site online behavior clickstream data collection method commonly used in web analytics). The importance of data quality of Big Data is emphasized through the evaluation of JavaScript tracking. The Total Survey Error framework is applied to JavaScript tracking and 17 nonsampling error sources are identified and evaluated. The bias imposed by these error sources varies from large to small, but the major takeaway is
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Kim, Jin Mo. "Name matching for data quality mediator." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/36588.

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Viklund, Adam. "Data Quality Study of AMR Systems." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-269465.

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Energy metering is a constantly changing field with increasing demands to get more measurement data. The implications are systems that are evolving and improving. It is important for data to be of high quality in these systems. This thesis set out to investigate data quality in advanced meter reading (AMR) systems that are used by energy companies in Sweden today. In order to investigate data quality, a definition was suggested. The definition was used as a basis for interviewing users of AMR systems to figure out the user experience of data quality and to understand what features improve data
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Aljumaili, Mustafa. "Data Quality Assessment : Applied in Maintenance." Doctoral thesis, Luleå tekniska universitet, Drift, underhåll och akustik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-26088.

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Godkänd; 2016; 20160126 (musalj); Nedanstående person kommer att disputera för avläggande av teknologie doktorsexamen. Namn: Mustafa Aljumaili Ämne: Drift och underhållsteknik/Operation and Maintenance Engineering Avhandling: Data Quality Assessment: Applied in Maintenance Opponent: Docent Mirka Kans, Institutionen för Maskinteknik, Linnéuniversitetet, Växjö. Ordförande: Professor Uday Kumar, Avdelning för Drift, underhåll och akustik, Institutionen för samhällsbyggnad och naturresurser, Luleå tekniska universitet. Tid: Fredag 4 mars 2016, kl 10.00 Plats: F1031, Luleå te
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Edwards, Matthew. "Data quality measures for identity resolution." Thesis, Lancaster University, 2018. http://eprints.lancs.ac.uk/124402/.

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The explosion in popularity of online social networks has led to increased interest in identity resolution from security practitioners. Being able to connect together the multiple online accounts of a user can be of use in verifying identity attributes and in tracking the activity of malicious users. At the same time, privacy researchers are exploring the same phenomenon with interest in identifying privacy risks caused by re-identification attacks. Existing literature has explored how particular components of an online identity may be used to connect profiles, but few if any studies have atte
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Zhu, Zhaochen. "Computational methods in air quality data." HKBU Institutional Repository, 2017. https://repository.hkbu.edu.hk/etd_oa/402.

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In this thesis, we have investigated several computational methods on data assimilation for air quality prediction, especially on the characteristic of sparse matrix and the underlying information of gradient in the concentration of pollutant species. In the first part, we have studied the ensemble Kalman filter (EnKF) for chemical species simulation in air quality forecast data assimilation. The main contribution of this paper is to study the sparse data observations and make use of the matrix structure of the Kalman filter updated equations to design an algorithm to compute the analysis of c
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Nitesh, Varma Rudraraju Nitesh, and Boyanapally Varun Varun. "Data Quality Model for Machine Learning." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18498.

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Context: - Machine learning is a part of artificial intelligence, this area is now continuously growing day by day. Most internet related services such as Social media service, Email Spam, E-commerce sites, Search engines are now using machine learning. The Quality of machine learning output relies on the input data, so the input data is crucial for machine learning and good quality of input data can give a better outcome to the machine learning system. In order to achieve quality data, a data scientist can use a data quality model on data of machine learning. Data quality model can help data
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Issa, Subhi. "Linked data quality : completeness and conciseness." Electronic Thesis or Diss., Paris, CNAM, 2019. http://www.theses.fr/2019CNAM1274.

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La large diffusion des technologies du Web Sémantique telles que le Resource Description Framework (RDF) permet aux individus de construire leurs bases de données sur le Web, d'écrire des vocabulaires et de définir des règles pour organiser et expliquer les relations entre les données selon les principes des données liées. En conséquence, une grande quantité de données structurées et interconnectées est générée quotidiennement. Un examen attentif de la qualité de ces données pourrait s'avérer très critique, surtout si d'importantes recherches et décisions professionnelles en dépendent. La qual
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Daley, Caitlin Marie. "Application of Data Mining Tools for Exploring Data: Yarn Quality Case Study." NCSU, 2008. http://www.lib.ncsu.edu/theses/available/etd-10292008-165755/.

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Businesses are constantly striving for a competitive edge in the economy, and data-driven decision making is crucial to achieve this goal. Four data mining tools, principal component analysis, cluster analysis, recursive partitioning, and discriminant analysis, were used to explore the major factors that contribute to ends down in a rotor spinning manufacturing process. Principal component analysis was used to explore the research question about whether the large number of cotton properties used to classify cotton could be reduced to a significant few. Cluster analysis was used to gain insight
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Gibson, Nicola. "Measuring the quality of patient data with particular reference to data accuracy." Thesis, Keele University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.363751.

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Health Authorities receive vast quantities of data from providers relating to patients treated. Ibis data is used to survey the health of the resident population and to determine future healthcare services. It is therefore essential that the quality of this data is measured. North Staffordshire Health Authority already monitor, to a certain extent, the quality of data received. However, accuracy is one attribute of quality not monitored. This thesis proposes a method to measure the accuracy of patient data, in particular clinical coding. The traditional method of measuring accuracy determines
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Coutinho, Maria da Graça de Tavares e. Távora Pereira. "Analysing data from pension schemes : data quality and relevance for actuarial valuations." Master's thesis, Instituto Superior de Economia e Gestão, 2019. http://hdl.handle.net/10400.5/19018.

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Mestrado em Actuarial Science<br>Os dados são o objeto de uma análise atuarial. O primeiro passo de uma avaliação é a revisão dos dados, juntamente com a definição dos pressupostos necessários e tendo conhecimento da teoria atuarial - estas componentes juntas permitirão ao atuário realizar os cálculos necessários e interpretar os resultados obtidos. Tendo isto em consideração, a qualidade dos dados sobressaiu como um elemento fundamental, tendo sido o tema escolhido para este trabalho. Depois de um estágio no escritório de Lisboa da Willis Towers Watson, percebi que os dados são um campo bas
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He, Yingjie. "Data hovering algorithm for improving data retention and data quality in energy-constrained mobile wireless sensor networks." Thesis, University of Newcastle Upon Tyne, 2012. http://hdl.handle.net/10443/1453.

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A Wireless Sensor Network (WSN) is composed of numerous spatially distributed, low cost, low power and multifunctional sensor nodes which can be used to monitor the surrounding environment. In mobile networks, the sensed data collected by the sensor nodes may move out of the area where it has been gathered (area of origin) with its carrying node. A problem may arise in this situation: when requesting the historical information of a specific area, it is possible that none of the nodes currently located in such area can provide the required information. This thesis addresses the issue of retaini
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Kara, Madjid. "Data quality for the decision of the ambient systems." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLV009.

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La qualité des données est une condition commune à tous les projets de technologie de l'information, elle est devenue un domaine de recherche complexe avec la multiplicité et l’expansion des différentes sources de données. Des chercheurs se sont penchés sur l’axe de la modélisation et l’évaluation des données, plusieurs approches ont été proposées mais elles étaient limitées à un domaine d’utilisation bien précis et n’offraient pas un profil de qualité nous permettant d’évaluer un modèle de qualité de données global. L’évaluation basée sur les modèles de qualité ISO a fait son apparition, néan
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Huang, Shiping. "Exploratory visualization of data with variable quality." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-01115-225546/.

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Liebchen, Gernot Armin. "Data cleaning techniques for software engineering data sets." Thesis, Brunel University, 2010. http://bura.brunel.ac.uk/handle/2438/5951.

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Data quality is an important issue which has been addressed and recognised in research communities such as data warehousing, data mining and information systems. It has been agreed that poor data quality will impact the quality of results of analyses and that it will therefore impact on decisions made on the basis of these results. Empirical software engineering has neglected the issue of data quality to some extent. This fact poses the question of how researchers in empirical software engineering can trust their results without addressing the quality of the analysed data. One widely accepted
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Furlani, Simone <1992&gt. "The issue of data quality on data-driven strategies: Challenges and best practices." Master's Degree Thesis, Università Ca' Foscari Venezia, 2016. http://hdl.handle.net/10579/8733.

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In the digitalised economy of today we are witnessing an era in which companies, from any sector, are collecting huge volumes of digital information. In a competitive context in which the analysis of data promises strategic advantages, the issue of data quality is more important than ever. Better data quality is needed not only because it drives to better decisions, but also because surging regulatory requirements increase the pressure on companies for more transparency and higher-quality standards of information. This qualitative research tries to identify the main issues related to data qual
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Gupta, Ragini. "A Framework for Data Quality for Synthetic Information." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/49675.

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Data quality has been an area of increasing interest for researchers in recent years due to the rapid emergence of 'big data' processes and applications. In this work, the data quality problem is viewed from the standpoint of synthetic information. Based on the structure and complexity of synthetic data, a need to have a data quality framework specific to it was realized. This thesis presents this framework along with implementation details and results of a large synthetic dataset to which the developed testing framework is applied. A formal conceptual framework was designed for assessing data
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44

Cui, Qingguang. "Measuring data abstraction quality in multiresolution visualizations." Worcester, Mass. : Worcester Polytechnic Institute, 2007. http://www.wpi.edu/Pubs/ETD/Available/etd-041107-224152/.

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45

Baalbaki, Hussein. "Designing Big Data Frameworks for Quality-of-Data Controlling in Large-Scale Knowledge Graphs." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS697.

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Les Knowledge Graphs (KG) sont la représentation la plus utilisée d'informations structurées sur un domaine particulier, composée de milliards de faits sous la forme d'entités (nœuds) et de relations (bords) entre eux. De plus, les informations de type sémantique des entités sont également contenues dans les KG. Le nombre de KG n'a cessé d'augmenter au cours des 20 dernières années dans divers domaines, notamment le gouvernement, la recherche universitaire, les domaines biomédicaux, etc. Les applications basées sur l'apprentissage automatique qui utilisent les KG incluent la liaison d'entités,
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Schmidt, Sven. "Quality of service aware data stream processing." Doctoral thesis, [S.l.] : [s.n.], 2007. http://deposit.ddb.de/cgi-bin/dokserv?idn=983780625.

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Tardif, Geneviève. "Multivariate Analysis of Canadian Water Quality Data." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32245.

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Physical-chemical water quality data from lotic water monitoring sites across Canada were integrated into one dataset. Two overlapping matrices of data were analyzed with principal component analysis (PCA) and cluster analysis to uncover structure and patterns in the data. The first matrix (Matrix A) had 107 sites located throughout Canada, and the following water quality parameters: pH, specific conductance (SC), and total phosphorus (TP). The second matrix (Matrix B) included more variables: calcium (Ca), chloride (Cl), total alkalinity (T_ALK), dissolved oxygen (DO), water temperature (WT),
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48

Smith, Sonya K. "Assessing the quality of deep seismic data." Thesis, University of Cambridge, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361690.

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Karamancı, Kaan. "Exploratory data analysis for preemptive quality control." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/53126.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.<br>Includes bibliographical references (p. 113).<br>In this thesis, I proposed and implemented a methodology to perform preemptive quality control on low-tech industrial processes with abundant process data. This involves a 4 stage process which includes understanding the process, interpreting and linking the available process parameter and quality control data, developing an exploratory data toolset and presenting the findings in a visual and easily implementable fashion. In pa
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Schnetzer, Matthias, Franz Astleithner, Predrag Cetkovic, Stefan Humer, Manuela Lenk, and Mathias Moser. "Quality Assessment of Imputations in Administrative Data." De Gruyter, 2015. http://dx.doi.org/10.1515/JOS-2015-0015.

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This article contributes a framework for the quality assessment of imputations within a broader structure to evaluate the quality of register-based data. Four quality-related hyperdimensions examine the data processing from the raw-data level to the final statistics. Our focus lies on the quality assessment of different imputation steps and their influence on overall data quality. We suggest classification rates as a measure of accuracy of imputation and derive several computational approaches. (authors' abstract)
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