Ils utilisent g\u00e9n\u00e9ralement des pipelines de donn\u00e9es point \u00e0 point pour d\u00e9placer les donn\u00e9es entre les bases de donn\u00e9es op\u00e9rationnelles et un entrep\u00f4t de donn\u00e9es ou un data lake centralis\u00e9. Les pipelines ETL (extraire, transformer et charger), par exemple, prennent des donn\u00e9es, les transforment en lots r\u00e9guliers et les transmettent plus tard \u00e0 un entrep\u00f4t de donn\u00e9es analytique en aval. Les pipelines ETL et les pipelines ETL invers\u00e9s renvoient \u00e9galement les r\u00e9sultats des analyses de donn\u00e9es effectu\u00e9es dans l'entrep\u00f4t vers les bases de donn\u00e9es et les applications op\u00e9rationnelles.<\/p>\n\n\n\n
M\u00eame si les entreprises exploitent aujourd'hui souvent des dizaines, voire des centaines de pipelines de donn\u00e9es point \u00e0 point, de plus en plus de responsables informatiques en arrivent \u00e0 la conclusion que les pipelines de donn\u00e9es point \u00e0 point et par lots ne sont plus d'actualit\u00e9. Les anciens pipelines ne sont g\u00e9n\u00e9ralement pas tr\u00e8s flexibles et sont per\u00e7us par les d\u00e9veloppeurs comme des \"bo\u00eetes noires\", car ils ne peuvent pas \u00eatre adapt\u00e9s et sont difficiles \u00e0 transf\u00e9rer dans d'autres environnements. Lorsque des processus op\u00e9rationnels ou des donn\u00e9es doivent \u00eatre adapt\u00e9s, les d\u00e9veloppeurs de donn\u00e9es \u00e9vitent donc de modifier les pipelines existants. Au lieu de cela, ils ajoutent encore plus de pipelines et les dettes techniques qui y sont li\u00e9es. En fin de compte, les pipelines ETL traditionnels n\u00e9cessitent trop de puissance de calcul et d'espace de stockage, ce qui peut entra\u00eener des probl\u00e8mes d'\u00e9volutivit\u00e9 et de performance ainsi que des co\u00fbts d'exploitation \u00e9lev\u00e9s \u00e0 mesure que le volume de donn\u00e9es et les exigences augmentent.<\/p>\n\n\n\n
Les pipelines de donn\u00e9es en continu constituent une approche moderne de la fourniture de donn\u00e9es en tant que produit en libre-service. Au lieu d'envoyer des donn\u00e9es \u00e0 un entrep\u00f4t central ou \u00e0 un outil d'analyse, les pipelines de flux de donn\u00e9es peuvent capturer les changements en temps r\u00e9el, les enrichir au fil de l'eau et les envoyer \u00e0 des syst\u00e8mes en aval. Les \u00e9quipes peuvent traiter, partager et r\u00e9utiliser les donn\u00e9es o\u00f9 et quand elles en ont besoin, avec leur propre acc\u00e8s en libre-service.\u00a0<\/p>\n\n\n\n
Contrairement aux pipelines ordinaires, les pipelines de flux de donn\u00e9es peuvent \u00eatre cr\u00e9\u00e9s avec des langages d\u00e9claratifs comme SQL. Cela permet d'\u00e9viter les t\u00e2ches op\u00e9rationnelles inutiles avec une logique pr\u00e9d\u00e9finie des op\u00e9rations requises. Cette approche contribue \u00e0 maintenir l'\u00e9quilibre entre l'observabilit\u00e9 continue centralis\u00e9e, la s\u00e9curit\u00e9, la gestion des politiques, les normes de conformit\u00e9 et le besoin de donn\u00e9es faciles \u00e0 rechercher et \u00e0 trouver.<\/p>\n\n\n\n
confluent.io<\/a><\/p>","protected":false},"excerpt":{"rendered":" Pour faciliter l'acc\u00e8s \u00e0 ces donn\u00e9es, la plupart des d\u00e9partements informatiques centralisent autant d'informations que possible. 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Um den Zugriff auf diese Daten zu erleichtern, zentralisieren die meisten IT-Abteilungen so viele Informationen wie m\u00f6glich. <\/p>\n","category_list_v2":"IT-Management<\/a>, MAG 24-06<\/a>","author_info_v2":{"name":"E3 Magazine","url":"https:\/\/e3mag.com\/fr\/author\/e3_magazin\/"},"comments_num_v2":"0 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