Letteratura scientifica selezionata sul tema "Données massives – Gestion"
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Articoli di riviste sul tema "Données massives – Gestion"
Boelle, Pierre-Yves, Rodolphe Thiébaut e Dominique Costagliola. "Données massives, vous avez dit données massives ?" Questions de santé publique, n. 30 (settembre 2015): 1–4. http://dx.doi.org/10.1051/qsp/2015030.
Testo completode Certeau, Michel. "Économies Ethniques : Pour une École de la Diversité". Annales. Histoire, Sciences Sociales 41, n. 4 (agosto 1986): 789–815. http://dx.doi.org/10.3406/ahess.1986.283313.
Testo completoJullian-Desayes, Ingrid, Marie Joyeux-Faure, Sébastien Baillieul, Rita Guzun, Renaud Tamisier e Jean-Louis Pepin. "Quelles perspectives pour le syndrome d’apnées du sommeil et la santé connectée ?" L'Orthodontie Française 90, n. 3-4 (settembre 2019): 435–42. http://dx.doi.org/10.1051/orthodfr/2019019.
Testo completoHernández-Huerta, Arturo, Octavio Pérez-Maqueo e Miguel Equihua Zamora. "¿Puede el desarrollo ser sostenible, integral y coherente?" Regions and Cohesion 8, n. 3 (1 dicembre 2018): 1–14. http://dx.doi.org/10.3167/reco.2018.080302.
Testo completoHlatywayo, F., D. D. Marques, V. Chikwasha, A. Mandisodza, S. Shumbairerwa e S. T. Mangodza. "A Review of Massive Blood Transfusion and its Associated Syndromes in Zimbabwe". Africa Sanguine 22, n. 1 (20 agosto 2020): 23–30. http://dx.doi.org/10.4314/asan.v22i1.4.
Testo completoFujiki, Kenji, e Mélanie Laleau. "Une approche géographique pour spatialiser les besoins en hébergements d'urgence en situation de crise : une étude appliquée au cas d'une évacuation massive provoquée par une crue majeure de la seine en région francilienne". La Houille Blanche, n. 3-4 (ottobre 2019): 75–83. http://dx.doi.org/10.1051/lhb/2019043.
Testo completoChapman, Craig S. "Force Projection in the Time of Scurvy: The Destruction of the 1740-42 West Indies Expedition". Northern Mariner / Le marin du nord 33, n. 1 (27 luglio 2023): 27–42. http://dx.doi.org/10.25071/2561-5467.1081.
Testo completoSombié, Issa, David O. S. Ilboudo, André Kamba Soubeiga e Helle Samuelsen. "Comprendre l’influence des facteurs contextuels sur la participation communautaire à la santé : une étude de cas dans le district sanitaire de Tenkodogo, au Burkina Faso". Global Health Promotion 24, n. 3 (7 agosto 2015): 87–95. http://dx.doi.org/10.1177/1757975915591685.
Testo completoSzabo, Denis. "Vie urbaine et criminalité". III. Aspects de la vie urbaine 9, n. 1-2 (12 aprile 2005): 67–81. http://dx.doi.org/10.7202/055393ar.
Testo completoGizzi, Chiara. "Open Licensing et patrimoine." Informationswissenschaft: Theorie, Methode und Praxis 6, n. 1 (9 luglio 2020): 150–81. http://dx.doi.org/10.18755/iw.2020.8.
Testo completoTesi sul tema "Données massives – Gestion"
Dia, Amadou Fall. "Filtrage sémantique et gestion distribuée de flux de données massives". Electronic Thesis or Diss., Sorbonne université, 2018. http://www.theses.fr/2018SORUS495.
Testo completoOur daily use of the Internet and related technologies generates, at a rapid and variable speeds, large volumes of heterogeneous data issued from sensor networks, search engine logs, multimedia content sites, weather forecasting, geolocation, Internet of Things (IoT) applications, etc. Processing such data in conventional databases (Relational Database Management Systems) may be very expensive in terms of time and memory storage resources. To effectively respond to the needs of rapid decision-making, these streams require real-time processing. Data Stream Management Systems (SGFDs) evaluate queries on the recent data of a stream within structures called windows. The input data are different formats such as CSV, XML, RSS, or JSON. This heterogeneity lock comes from the nature of the data streams and must be resolved. For this, several research groups have benefited from the advantages of semantic web technologies (RDF and SPARQL) by proposing RDF data streams processing systems called RSPs. However, large volumes of RDF data, high input streams, concurrent queries, combination of RDF streams and large volumes of stored RDF data and expensive processing drastically reduce the performance of these systems. A new approach is required to considerably reduce the processing load of RDF data streams. In this thesis, we propose several complementary solutions to reduce the processing load in centralized environment. An on-the-fly RDF graphs streams sampling approach is proposed to reduce data and processing load while preserving semantic links. This approach is deepened by adopting a graph-oriented summary approach to extract the most relevant information from RDF graphs by using centrality measures issued from the Social Networks Analysis. We also adopt a compressed format of RDF data and propose an approach for querying compressed RDF data without decompression phase. To ensure parallel and distributed data streams management, the presented work also proposes two solutions for reducing the processing load in distributed environment. An engine and parallel processing approaches and distributed RDF graphs streams. Finally, an optimized processing approach for static and dynamic data combination operations is also integrated into a new distributed RDF graphs streams management system
Castanié, Laurent. "Visualisation de données volumiques massives : application aux données sismiques". Thesis, Vandoeuvre-les-Nancy, INPL, 2006. http://www.theses.fr/2006INPL083N/document.
Testo completoSeismic reflection data are a valuable source of information for the three-dimensional modeling of subsurface structures in the exploration-production of hydrocarbons. This work focuses on the implementation of visualization techniques for their interpretation. We face both qualitative and quantitative challenges. It is indeed necessary to consider (1) the particular nature of seismic data and the interpretation process (2) the size of data. Our work focuses on these two distinct aspects : 1) From the qualitative point of view, we first highlight the main characteristics of seismic data. Based on this analysis, we implement a volume visualization technique adapted to the specificity of the data. We then focus on the multimodal aspect of interpretation which consists in combining several sources of information (seismic and structural). Depending on the nature of these sources (strictly volumes or both volumes and surfaces), we propose two different visualization systems. 2) From the quantitative point of view, we first define the main hardware constraints involved in seismic interpretation. Focused on these constraints, we implement a generic memory management system. Initially able to couple visualization and data processing on massive data volumes, it is then improved and specialised to build a dynamic system for distributed memory management on PC clusters. This later version, dedicated to visualization, allows to manipulate regional scale seismic data (100-200 GB) in real-time. The main aspects of this work are both studied in the scientific context of visualization and in the application context of geosciences and seismic interpretation
Castelltort, Arnaud. "Historisation de données dans les bases de données NoSQLorientées graphes". Thesis, Montpellier 2, 2014. http://www.theses.fr/2014MON20076.
Testo completoThis thesis deals with data historization in the context of graphs. Graph data have been dealt with for many years but their exploitation in information systems, especially in NoSQL engines, is recent. The emerging Big Data and 3V contexts (Variety, Volume, Velocity) have revealed the limits of classical relational databases. Historization, on its side, has been considered for a long time as only linked with technical and backups issues, and more recently with decisional reasons (Business Intelligence). However, historization is now taking more and more importance in management applications.In this framework, graph databases that are often used have received little attention regarding historization. Our first contribution consists in studying the impact of historized data in management information systems. This analysis relies on the hypothesis that historization is taking more and more importance. Our second contribution aims at proposing an original model for managing historization in NoSQL graph databases.This proposition consists on the one hand in elaborating a unique and generic system for representing the history and on the other hand in proposing query features.We show that the system can support both simple and complex queries.Our contributions have been implemented and tested over synthetic and real databases
Baron, Benjamin. "Transport intermodal de données massives pour le délestage des réseaux d'infrastructure". Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066454/document.
Testo completoIn this thesis, we exploit the daily mobility of vehicles to create an alternative transmission medium. Our objective is to draw on the many vehicular trips taken by cars or public transports to overcome the limitations of conventional data networks such as the Internet. In the first part, we take advantage of the bandwidth resulting from the mobility of vehicles equipped with storage capabilities to offload large amounts of delay-tolerant traffic from the Internet. Data is transloaded to data storage devices we refer to as offloading spots, located where vehicles stop often and long enough to transfer large amounts of data. Those devices act as data relays, i.e., they store data it is until loaded on and carried by a vehicle to the next offloading spot where it can be dropped off for later pick-up and delivery by another vehicle. We further extend the concept of offloading spots according to two directions in the context of vehicular cloud services. In the first extension, we exploit the storage capabilities of the offloading spots to design a cloud-like storage and sharing system for vehicle passengers. In the second extension, we dematerialize the offloading spots into pre-defined areas with high densities of vehicles that meet long enough to transfer large amounts of data. The performance evaluation of the various works conducted in this thesis shows that everyday mobility of entities surrounding us enables innovative services with limited reliance on conventional data networks
Baron, Benjamin. "Transport intermodal de données massives pour le délestage des réseaux d'infrastructure". Electronic Thesis or Diss., Paris 6, 2016. http://www.theses.fr/2016PA066454.
Testo completoIn this thesis, we exploit the daily mobility of vehicles to create an alternative transmission medium. Our objective is to draw on the many vehicular trips taken by cars or public transports to overcome the limitations of conventional data networks such as the Internet. In the first part, we take advantage of the bandwidth resulting from the mobility of vehicles equipped with storage capabilities to offload large amounts of delay-tolerant traffic from the Internet. Data is transloaded to data storage devices we refer to as offloading spots, located where vehicles stop often and long enough to transfer large amounts of data. Those devices act as data relays, i.e., they store data it is until loaded on and carried by a vehicle to the next offloading spot where it can be dropped off for later pick-up and delivery by another vehicle. We further extend the concept of offloading spots according to two directions in the context of vehicular cloud services. In the first extension, we exploit the storage capabilities of the offloading spots to design a cloud-like storage and sharing system for vehicle passengers. In the second extension, we dematerialize the offloading spots into pre-defined areas with high densities of vehicles that meet long enough to transfer large amounts of data. The performance evaluation of the various works conducted in this thesis shows that everyday mobility of entities surrounding us enables innovative services with limited reliance on conventional data networks
Gueye, Ndeye. "Une démarche de gestion stratégique et opérationnelle du changement dans le contexte de l'exploitation avancée de données massives internes aux organisations". Master's thesis, Université Laval, 2017. http://hdl.handle.net/20.500.11794/30367.
Testo completoGarmaki, Mahda. "La capacité des "Big Data Analytics" et la création de valeur : l’effet médiateur de l’apprentissage organisationnel sur la performance des entreprises". Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLE018.
Testo completoThe purpose of this grounded theory research is to explore ‘to which extent firms can achieve value from big data analytics (BDA), in order to improve firm performance’. BDA is dramatically influencing the way firms perform and compete within the digital era. In this light, BDA has become the trending issue that generates innovative solutions and valuable insights through predictive approach. Despite the hype surrounding BDA value creation, it has not fully understood the features drive value and sustain competitive advantage from BDA. Using the classic grounded theory, this thesis conducted interviews with twenty-two executives from different firms. Through substantive theory, BDA capability is conceptualized as the core competency, which enables firms to accomplish value from BDA, transform the business into the data-driven approach, and subsequently enhance firm performance over-time. The core contribution of this grounded theory research focuses on capability building to implement and manipulate BDA. The findings of this study contribute to the knowledge of BDA value creation and digitalization through the following discussions: 1) while the conventional approach about BDA focuses data collection or investment on technologies, the findings indicate the various dimensions (internal and external resources and capabilities) should jointly contribute to building the overall BDA,2) furthermore, these dimensions and their properties create the integrative network, which is incomplete in the absence of individual dimension or their properties, 3) To identify the variables that are influenced by BDA capability, enhancing organizational learning is introduced as the “hidden value” of BDA capability, which is the dynamic process, and consequently develops sustained competitive advantage, 4) Within the digital era, BDA is the primary digital asset, as well as, digital lever. In this light, BDA capability fosters digital transformation through providing prerequisite capabilities, 5) Drawing resource-based view, knowledge-based view, and dynamic capability the conceptual model of this research is addressed through the combination of different resources (tangible intangible and personnel-based resources) and capabilities.The conceptual model demonstrates the direct effect of BDA capability on firm performance, as well as, the indirect effect that is mediated by organizational learning
Barry, Mariam. "Adaptive Scalable Online Learning for Handling Heterogeneous Streaming Data in Large-Scale Banking Infrastructure". Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAT006.
Testo completoArtificial Intelligence (AI) is a powerful tool to extract valuable insights for decision-making. However, learning from heterogeneous and unstructured streaming data presents a multitude of challenges that this research aims to tackle. The creation of big data is projected to experience exponential growth, with expectations to surpass 2,000 zettabytes by the year 2035. Such Big Data highlights the importance of efficient, incremental, and adaptive models. Online Learning, known as Streaming Machine Learning (SML), is a dynamic technique for building and updating learning models as new data arrive, without the need for periodic complete model replacement. It is the most efficient technique for big data stream learning. The change detection task is a proactive way to detect and prevent critical events such as cyber-attacks, fraud detection, or IT incidents in an online fashion. The research conducted during this thesis aims to develop adaptive and scalable online machine-learning solutions to learn from heterogeneous streaming data that can be operationalized with large-scale infrastructures, particularly in the banking sector. This Ph.D. thesis delves into algorithmic and infrastructure challenges related to continuous training and serving online machine learning over high-velocity streaming data from diverse sources, specifically focusing on large-scale IT infrastructures (AIOps). Thesis contributions include techniques like StreamFlow for summarizing information from big data streams, Stream2Graph for dynamically building and updating knowledge graphs for batch and online learning tasks, and StreamChange, an efficient and explainable online change detection model. Evaluation results on real-world open data and industrial data demonstrate performance improvements in learned models. StreamChange surpasses state-ofthe-art techniques in detecting gradual and abrupt changes. Additionally, the thesis introduces a conceptual framework, StreamMLOps, for scaling and serving online machine learning in real-time without pausing the inference pipeline. This framework showcases the effectiveness of the proposed MLOps pipeline on a feature-evolving dataset with millions of dimensions for malicious event detection tasks. Finally, we share lessons learned regarding Streaming Machine Learning systems, AI at scale, and online model management in large-scale banking, with a focus on streaming data and real-time applications
Brahem, Mariem. "Optimisation de requêtes spatiales et serveur de données distribué - Application à la gestion de masses de données en astronomie". Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLV009/document.
Testo completoThe big scientific data generated by modern observation telescopes, raises recurring problems of performances, in spite of the advances in distributed data management systems. The main reasons are the complexity of the systems and the difficulty to adapt the access methods to the data. This thesis proposes new physical and logical optimizations to optimize execution plans of astronomical queries using transformation rules. These methods are integrated in ASTROIDE, a distributed system for large-scale astronomical data processing.ASTROIDE achieves scalability and efficiency by combining the benefits of distributed processing using Spark with the relevance of an astronomical query optimizer.It supports the data access using the query language ADQL that is commonly used.It implements astronomical query algorithms (cone search, kNN search, cross-match, and kNN join) tailored to the proposed physical data organization.Indeed, ASTROIDE offers a data partitioning technique that allows efficient processing of these queries by ensuring load balancing and eliminating irrelevant partitions. This partitioning uses an indexing technique adapted to astronomical data, in order to reduce query processing time
Hatia, Saalik. "Leveraging formal specification to implement a database backend". Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS137.
Testo completoConceptually, a database storage backend is just a map of keys to values. However, to provide performance and reliability, a modern store is a complex, concurrent software system, opening many opportunities for bugs. This thesis reports on our journey from formal specification of a store to its implementation. The specification is terse and unambiguous, and helps reason about correctness. Read as pseudocode, the specification provides a rigorous grounding for implementation. The specification describes a store as a simple transactional shared memory, with two (behaviourally equivalent) variants, map- and journal-based. We implement these two basic variants verbatim in Java. We specify the features of a modern store, such as a write-ahead log with checkpointing and truncation, as a dynamic composition of instances of the two basic variants. The specification of correct composition is particularly simple. Our experimental evaluation of an implementation has acceptable performance, while our rigorous methodology increases confidence in its correctness
Libri sul tema "Données massives – Gestion"
Meier, Patrick. Digital Humanitarians: How Big Data Is Changing the Face of Humanitarian Response. Taylor & Francis Group, 2015.
Cerca il testo completoMeier, Patrick. Digital Humanitarians. Taylor & Francis Group, 2015.
Cerca il testo completoMeier, Patrick. Digital Humanitarians: How Big Data Is Changing the Face of Humanitarian Response. Taylor & Francis Group, 2015.
Cerca il testo completoMeier, Patrick. Digital Humanitarians: How Big Data Is Changing the Face of Humanitarian Response. Taylor & Francis Group, 2015.
Cerca il testo completoCrickard, Paul. Data Engineering with Python: Work with Massive Datasets to Design Data Models and Automate Data Pipelines Using Python. Packt Publishing, Limited, 2020.
Cerca il testo completoCapitoli di libri sul tema "Données massives – Gestion"
COHEN-BOULAKIA, Sarah, e Frédéric LEMOINE. "Workflows d’intégration de données bioinformatiques". In Intégration de données biologiques, 63–97. ISTE Group, 2022. http://dx.doi.org/10.51926/iste.9030.ch3.
Testo completoRapporti di organizzazioni sul tema "Données massives – Gestion"
McAdams-Roy, Kassandra, Philippe Després e Pierre-Luc Déziel. La gouvernance des données dans le domaine de la santé : Pour une fiducie de données au Québec ? Observatoire international sur les impacts sociétaux de l’intelligence artificielle et du numérique, febbraio 2023. http://dx.doi.org/10.61737/nrvw8644.
Testo completoMartineau, Joé T., Frédérique Romy Godin, Janine Badr, Alexandre Castonguay, Martin Cousineau, Philippe Després, Aude Motulsky, Jean Noel Nikiema, Cécile Petitgand e Catherine Régis. Enjeux éthiques de l’IA en santé - Fiche 4. Observatoire international sur les impacts sociétaux de l'IA et du numérique, marzo 2022. http://dx.doi.org/10.61737/fspn5441.
Testo completo