Data exhaust or exhaust data is the trail of data left by the activities of an Internet or other computer system users during their online activity, behavior, and transactions. This is part of a broader category of unconventional data that includes geospatial, network, and time-series data and may be useful for predictive analytics. Every visited website, clicked link, and even hovering with a mouse is collected, leaving behind a trail of data. An enormous amount of often raw data are created, which can be in the form of cookies, temporary files, logfiles, storable choices, and more. This information can help to improve the online experience, for example through customized content. It can be used to improve tracking trends and studying data exhaust also improves the user interface and the
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| - Data exhaust (en)
- Sillage de données (fr)
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| - Data exhaust or exhaust data is the trail of data left by the activities of an Internet or other computer system users during their online activity, behavior, and transactions. This is part of a broader category of unconventional data that includes geospatial, network, and time-series data and may be useful for predictive analytics. Every visited website, clicked link, and even hovering with a mouse is collected, leaving behind a trail of data. An enormous amount of often raw data are created, which can be in the form of cookies, temporary files, logfiles, storable choices, and more. This information can help to improve the online experience, for example through customized content. It can be used to improve tracking trends and studying data exhaust also improves the user interface and the (en)
- Le terme sillage de données fait référence aux traces laissées par les activités d’un internaute lors de la navigation en ligne. Une énorme quantité de données sont ainsi générées, souvent à l'état brut. Ces données (qui prennent la forme de cookies, fichiers temporaires, fichiers journaux) peuvent servir à l’amélioration de son expérience en ligne (par exemple la personnalisation de contenu). Mais offrant un aperçu précieux des habitudes d’un internaute, ces données sont également de valeur à des fins commerciales. (fr)
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| - Data exhaust or exhaust data is the trail of data left by the activities of an Internet or other computer system users during their online activity, behavior, and transactions. This is part of a broader category of unconventional data that includes geospatial, network, and time-series data and may be useful for predictive analytics. Every visited website, clicked link, and even hovering with a mouse is collected, leaving behind a trail of data. An enormous amount of often raw data are created, which can be in the form of cookies, temporary files, logfiles, storable choices, and more. This information can help to improve the online experience, for example through customized content. It can be used to improve tracking trends and studying data exhaust also improves the user interface and the layout design. On the other hand, they can also compromise privacy, as they offer a valuable insight into the user's habits. For example, as the world's most popular website, Google, uses this data exhaust to refine the predictive value of their products. The data that is collected by companies is often information that does not seem immediately useful. Although the information is not used by the company right away, it can be stored for future use or sold to someone else who can use the information. The data can help with quality control, performance, and revenue. Unlike primary content, these data are not purposefully created by the user, who is often unaware of their very existence. A bank for example would consider as primary data information concerning the sums and parties of a transaction, whilst secondary data might include the percentage of transactions carried out at a cash machine instead of a real bank. (en)
- Le terme sillage de données fait référence aux traces laissées par les activités d’un internaute lors de la navigation en ligne. Une énorme quantité de données sont ainsi générées, souvent à l'état brut. Ces données (qui prennent la forme de cookies, fichiers temporaires, fichiers journaux) peuvent servir à l’amélioration de son expérience en ligne (par exemple la personnalisation de contenu). Mais offrant un aperçu précieux des habitudes d’un internaute, ces données sont également de valeur à des fins commerciales. À la différence du contenu primaire, ces données ne sont pas activement créées par l’internaute, qui souvent ne se rend pas même compte de leur existence. Par exemple, une banque considérait comme primaires toutes les données en lien avec les montants et les destinataires de transactions, alors que les données secondaires comprendraient le pourcentage de transactions effectuées à un guichet automatique au lieu d'une banque proprement dite. (fr)
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