Publication

Pas si "bad", le "Big data"

Antonin Danalet
2015
Poster talk

Abstract

Le "Big Data" est communément associé à lexploitation de volumes massifs de données que nous générons, souvent à notre insu. En utilisant son téléphone mobile, en communiquant sur les réseaux sociaux, en questionnant des moteurs de recherche, ou encore en faisant des achats en ligne. Les objets que nous manipulons (véhicules, appareils électroménagers, cartes à puce, etc.) produisent aussi de nombreuses données exploitables. Si les craintes datteinte à la vie privée donnent une connotation négative au concept de "Big Data", celui-ci présente aussi des aspects positifs. Par exemple en épidémiologie pour traquer des virus, ou en urbanisme pour améliorer le fonctionnement des villes ("smart cities"). Et si le "Big Data" cachait plus de bons côtés quil nen a lair ?

Official source

https://infoscience.epfl.ch/record/213622?ln=en

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Related concepts (5)

Big data

Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.

Data

In common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.

Data science

Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data. Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.

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