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production mais surtout inscrits dans son ADN même. Depuis 2018, l’équipe data de BMW s’est engagée dans un parcours de transformation, défini par son Cloud Data Hub (CDH) : regrouper toutes les informations extraites des données à l’échelle de l’entreprise.\u003C/p\u003E\n\u003Cp\u003ELe principe directeur du CDH a toujours été de fournir un ensemble décentralisé d’outils data haut de gamme, le tout soutenu par un modèle central de gouvernance des données qui assure leur concordance et leur qualité.\u003C/p\u003E\n\u003Cp\u003EL’entreprise collecte d’énormes volumes de données diverses et variées (quelque 6 000 jeux de données et produits couvrant 15 domaines de BMW, dont les processus d’entretien, de construction et après-vente), auxquelles plus de 10 000 utilisateurs accèdent chaque mois. 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Sur ce point, Snowflake se démarquait de ses concurrents. C’est pour cette raison que nous avons décidé d’intégrer Snowflake dans le CDH. »\u003C/p\u003E\n\u003Cp\u003EMaintenant que l’AI Data Cloud constitue un composant clé de son socle data, BMW Group profite de performances élevées pour exécuter ses charges de travail sur d’importants volumes de données. Par exemple, Snowflake héberge désormais dans un data lake massif les données d’entretien de l’entreprise, sur les transactions d’entretien et de réparation de la dernière décennie. Soutenus par la puissance de calcul de Snowflake, les garages et les concessions peuvent récupérer presque instantanément l’historique d’entretien de leurs clients. Ainsi, les collaborateurs peuvent travailler plus efficacement et obtenir les informations dont ils ont besoin plus rapidement, tandis que les clients bénéficient d’un entretien et de réparations plus rapides. \u003C/p\u003E\n\u003Cp\u003ESi Iceberg offre un meilleur rapport coûts-bénéfices pour les charges de travail simples sur des tables uniques, l’équipe CDH a rapidement compris que Snowflake pouvait fournir des performances élevées à moindre coût pour les charges de travail plus complexes. « Comme il s’agit d’une ressource de calcul haut de gamme, nous pensions que Snowflake nous coûterait plus cher, mais en fait nous réalisons des économies sur les charges de travail nécessitant beaucoup de calculs », souligne Ruben Simon. Ainsi, sur les charges de travail exécutées sur des données d’entretien, BMW Group a réduit ses coûts de 25 % en moyenne avec Snowflake par rapport à sa plateforme héritée.\u003C/p\u003E\n\u003Cp\u003EEn outre, l’interface de Snowflake est facile à utiliser et à configurer. Alors que les outils AWS obligent leurs utilisateurs à configurer des rôles, déployer des instances Snowflake ne prend que quelques clics. L’équipe CDH a collaboré étroitement avec Snowflake pour simplifier encore l’adoption de l’AI Data Cloud et les premiers pas de ses utilisateurs. Ces efforts expliquent sans doute son succès si rapide, puisque plus de 60 cas d’usage du CDH (ventes, entretien, supply chain, etc.) ont été mis en place et exécutés sur Snowflake en seulement 18 mois.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular"},"quote_item":{"id":"quote-item-d53ef6227a","alignment":"left","layout":"card","quoteSourceName":"Khalid Al-Khalili","quoteSourceTitle":"Big Data Architect, Cloud Data Hub, BMW Group","showQuoteIcon":true,"quote":"Les services cloud élastiques permettent de répondre à la demande, mais leur disponibilité n’est pas garantie face à des jeux de données volumineux. Lorsque nous avons soumis ces requêtes dans Snowflake, les performances ont été constantes. »\r\n","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"title_v2_copy_copy_8_191437395":{"id":"title-v2-f93cbc8ad0","type":"heading4","lines":["Un levier pour répondre aux besoins data de BMW, compatible avec son framework de gouvernance"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"blue-black-text-color"},"text_copy_copy_63041_306225306":{"id":"text-c637741cfe","text":"\u003Cp\u003EChaque outil intégré dans le CDH doit respecter le framework de gouvernance de BMW, ainsi que sa politique de stockage et de gestion des données. Snowflake n’a pas échappé à cette règle.\u003C/p\u003E\n\u003Cp\u003E« Dans notre framework de gouvernance, toutes les données sur notre plateforme doivent être transparentes », confie Khalid Al-Khalili. « Si un data steward autorise l’accès à un jeu de données sur un système, cette autorisation doit également s’appliquer aux autres plateformes, que ce soit AWS ou Snowflake. »\u003C/p\u003E\n\u003Cp\u003EEn pratique, cela signifie que Snowflake doit être en mesure de lire et d’écrire des données partout dans le CDH, ainsi que de consulter les identités sur les systèmes internes de BMW et dans AWS. Si ce niveau d’intégration sur l’ensemble du parc de données pouvait sembler inatteignable, BMW a su incorporer Snowflake dans son écosystème multifournisseur complexe avec une relative simplicité, en 18 mois. 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