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Imaginez devoir traverser un pays sans jamais l’avoir visité, sans connaître le terrain et ses difficultés et dangers éventuels, guidé uniquement par les panneaux et votre bon sens. C’est la même chose pour les entreprises : elles ne peuvent pas s’en remettre simplement à la foi et à des suppositions pour agir. Ainsi, les entreprises de toutes les tailles et de tous les secteurs ont besoin de données pour orienter leurs décisions et leurs campagnes et optimiser leurs activités. C’est là qu’entre en jeu \u003Ca href=\"https://www.snowflake.com/fr/product/analytics/\"\u003El’analyse de données\u003C/a\u003E.\u003C/p\u003E\n\u003Cp\u003EGrâce à l’analyse de données, les entreprises obtiennent les informations clés dont elles ont besoin pour évoluer, se développer et s’améliorer, au profit de leurs clients comme de leurs équipes internes. Sans ces informations, elles se font distancer par leurs concurrents qui augmentent leurs parts de marché en prenant des décisions intelligentes et en élaborant minutieusement des plans fondés sur des recherches.\u003C/p\u003E\n\u003Cp\u003EDans ce guide, nous allons présenter les différents types d’analyse de données et leurs avantages, quelques cas d’usage types ainsi que des outils courants d’analyse de données, afin de vous aider à commencer à prendre en compte les données dans vos décisions et analyses stratégiques.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy_":{"columnClassNames":{"container_copy_copy__480869401":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__373061683":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1444615495":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__222865509":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1413360324":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy_":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__455068363":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__659376865":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1500909857":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1978652079":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"rel",":items":{"container_copy_copy":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"what",":items":{"title_v2":{"id":"title-v2-74d0751398","additionalClasses":"headline-decoration","type":"heading2","lines":["En quoi consiste l’analyse de données ?"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-39ca61447b","text":"\u003Cp\u003EL’analyse de données est le processus consistant à examiner, collecter et analyser des données brutes afin d’en dégager des tendances et d’en tirer des conclusions. L’analyse de données soutient la croissance des entreprises, car elle les aide à prendre des décisions éclairées et à améliorer les performances de l’ensemble de leurs équipes. \u003C/p\u003E\n\u003Cp\u003EDivers outils et techniques sont utilisés pour recueillir et extraire des informations à partir des données, comme des feuilles de calcul, des \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-lake-vs-data-warehouse-vs-data-mart/\"\u003Edata warehouses\u003C/a\u003E et des langages de programmation. Tous les types d’informations peuvent être analysés à l’aide de ces techniques : indicateurs sur les réseaux sociaux, \u003Ca href=\"https://www.snowflake.com/fr/solutions/industries/healthcare-and-life-sciences/\"\u003Edossiers médicaux de patients\u003C/a\u003E, quantités de stock, etc. Quelle que soit la taille d’une entreprise, qu’elle dispose de data analysts dédiés ou non, n’importe quelle équipe peut utiliser des outils d’analyse de données courants pour extraire les informations dont elle a besoin. L’un des principaux avantages de l’analyse de données est qu’elle permet de parcourir une masse d’informations pour y trouver des tendances et des schémas qui, sans cela, se perdraient dans tout le bruit numérique.\u003C/p\u003E\n\u003Cp\u003EQue ce soit une entreprise de gaming qui analyse le comportement des joueurs, une \u003Ca href=\"https://www.snowflake.com/fr/solutions/industries/financial-services/\"\u003Ebanque\u003C/a\u003E qui scrute le comportement de ses clients pour détecter tout signe de fraude, ou encore un retailer qui prédit le prochain achat d’un client, l’analyse de données permet de créer des expériences personnalisées, d’atténuer les risques et d’augmenter la fidélité à la marque.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy_":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"a",":items":{"title_v2":{"id":"title-v2-169fb0cffa","additionalClasses":"headline-decoration","type":"heading2","lines":["Types d’analyse de données"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-5f2151dab9","text":"\u003Cp\u003EIl existe quatre types d’analyse de données qui se complètent les uns les autres pour comprendre les événements passés et influencer les résultats futurs à l’aide d’informations et de recommandations fondées sur des données.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E1. L’analyse descriptive : que s’est-il passé ?\u003C/h4\u003E\r\n\u003Cp\u003ECe type d’analyse résume des données historiques pour comprendre ce qui s’est passé sur une période donnée, par exemple, s’il y a eu une augmentation des mentions « J’aime » sur vos publications sur les réseaux sociaux, davantage de transactions dans un jeu, ou une baisse des ventes trimestrielles de produits. L’analyse descriptive correspond au niveau d’analyse le plus élémentaire.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E2. L’analyse diagnostique : pourquoi est-ce arrivé ?\u003C/h4\u003E\r\n\u003Cp\u003EC’est là que les choses deviennent un peu plus complexes et intéressantes. L’analyse diagnostique se concentre sur les raisons qui expliquent ces événements passés. Elle implique donc une combinaison d’entrées de données et de théories. Avez-vous utilisé la bonne combinaison de hashtags pour augmenter la visibilité de votre publication ? Un événement in-game à durée limitée a-t-il favorisé cette augmentation des transactions ?\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E3. L’analyse prédictive : que va-t-il se passer ?\u003C/h4\u003E\r\n\u003Cp\u003EMaintenant que vous avez répondu aux questions quoi et pourquoi, vous devez commencer à planifier ce que vous voulez faire à partir de là. \u003Ca href=\"https://www.snowflake.com/fr/fundamentals/predictive-analytics-marketing/\"\u003EL’analyse prédictive\u003C/a\u003E vous aide à comprendre ce qui risque de se produire ensuite. Si votre client a tendance à acheter de la litière pour chat à peu près tous les mois à la même période, il y a de fortes chances qu’il repasse à l’achat. Si le client d’une banque paye toujours ses factures à temps, celle-ci peut probablement lui faire confiance pour rembourser ses prêts.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E4. L’analyse prescriptive : que devons-nous faire ?\u003C/h4\u003E\r\n\u003Cp\u003EC’est là que vous pouvez commencer à traduire toutes les données et informations que vous avez recueillies et analysées en recommandations pour décider quelle sera votre prochaine action. Votre marque a connu une forte augmentation de ses ventes d’un mois sur l’autre, et votre dernier produit a été épuisé quelques minutes après son lancement ? Mettez donc en place un système de précommandes pour le prochain afin d’améliorer la satisfaction de vos clients.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__1444615495":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"use",":items":{"title_v2":{"id":"title-v2-cb8294b9b3","additionalClasses":"headline-decoration","type":"heading2","lines":["Avantages de l’analyse de données"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-9a30ca643d","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EUne stratégie d’analyse de données efficace peut transformer votre entreprise, grâce à une meilleure visibilité sur vos points forts et faibles. Elle comble le fossé entre les connaissances et l’action, afin de permettre à vos équipes d’optimiser leur efficacité et la satisfaction de vos clients. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E1. Prise de décision éclairée\u003C/h4\u003E\n\u003Cp\u003EPas de devinettes, pas de suppositions. Prenez des décisions basées sur des données en vous appuyant sur des preuves et des tendances extraites de jeux de données historiques pour obtenir des résultats plus précis et plus fiables.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E2. Amélioration de l’efficacité opérationnelle\u003C/h4\u003E\n\u003Cp\u003EComme on dit, le savoir, c’est le pouvoir. Ainsi, l’analyse de données fournit des informations exploitables qui permettent de repérer les inefficacités opérationnelles, les goulots d’étranglement et les améliorations possibles dans l’ensemble de l’entreprise. Les entreprises disposent ainsi des informations dont elles ont besoin pour simplifier leurs processus, réduire leurs coûts, améliorer leur productivité et abandonner ou affiner leurs stratégies inefficaces.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E3. Atténuation des risques\u003C/h4\u003E\n\u003Cp\u003EAlors que les fraudes toujours plus fréquentes continuent d’évoluer, les entreprises doivent rester vigilantes face aux acteurs malveillants. L’analyse de données leur permet d’identifier de manière proactive les menaces et les anomalies, afin de développer plus facilement des stratégies ciblées d’atténuation des risques grâce à l’IA et au machine learning.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E4. Meilleure compréhension des clients\u003C/h4\u003E\n\u003Cp\u003EL’analyse de données fournit aux entreprises les informations et données clients stratégiques dont elles ont besoin pour personnaliser l’expérience client, améliorer leurs produits et services et augmenter la satisfaction et la fidélité de leurs clients. Elle leur offre ainsi un avantage concurrentiel considérable qui favorise non seulement la fidélité de leurs clients existants, mais aussi l’acquisition de nouveaux clients et la croissance globale de l’entreprise.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__1978652079":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"benefits",":items":{"title_v2":{"id":"title-v2-9948b85040","additionalClasses":"headline-decoration","type":"heading2","lines":["Étapes d’analyse de données"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-1d06907312","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003ESi le fait de disposer d’une mine de données est déjà une excellente chose, il faut encore prendre certaines mesures pour passer des données brutes à des données exploitables. Un projet type d’analyse de données implique du travail tout au long du cycle de vie de l’analyse de données : définition de l’objectif, collecte des données, nettoyage et préparation des données, et enfin analyse. \u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E1. Définition de l’objectif\u003C/h4\u003E\r\n\u003Cp\u003EQuelles informations votre équipe espère-t-elle tirer des données que vous collectez ? Quel processus ou opération essayez-vous d’optimiser ? Quelle campagne soutenez-vous ? Il ne sert à rien de consacrer du temps et des ressources à recueillir une masse de données si vous n’avez pas d’objectifs clairs et définis. Définissez votre objectif pour déterminer les données dont vous avez besoin et comment les regrouper ou les dissocier.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E2. Collecte des données\u003C/h4\u003E\r\n\u003Cp\u003EMaintenant que vous savez exactement ce que vous recherchez, vos data analysts peuvent collecter les données pertinentes pour soutenir vos objectifs. Celles-ci peuvent être très variées : trafic sur votre site sur une période donnée, enquêtes auprès de vos clients, statistiques sur l’engagement sur les réseaux sociaux, données transactionnelles, évaluation des risques, etc.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E3. Nettoyage et préparation des données\u003C/h4\u003E\r\n\u003Cp\u003ENettoyez les données et examinez-les pour détecter les erreurs, les incohérences et les anomalies qui pourraient avoir un impact sur leur fiabilité et leur utilisation. Organisez-les ensuite pour faciliter leur analyse. Les feuilles de calcul sont idéales pour les jeux de données restreints, mais elles sont lentes et peu maniables pour traiter des jeux de données plus volumineux. Les outils de \u003Ca href=\"https://www.snowflake.com/fr/fundamentals/ai-for-business-intelligence/\"\u003EBusiness Intelligence\u003C/a\u003E (BI) sont idéaux pour la \u003Ca href=\"https://www.snowflake.com/fr/fundamentals/data-visualization/\"\u003Evisualisation de données\u003C/a\u003E et les tableaux de bord, tandis que les \u003Ca href=\"https://www.snowflake.com/fr/product/analytics/\"\u003Ebases de données et les data warehouses\u003C/a\u003E sont nécessaires pour les très grands jeux de données.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E4. Analyse des données\u003C/h4\u003E\r\n\u003Cp\u003EVous avez maintenant votre jeu de données propres et préparées. Il est temps de les analyser pour identifier les schémas, les relations et les tendances qui s’en dégagent à l’aide de techniques logiques et statistiques. Rappelez-vous des types d’analyse de données dont nous avons parlé précédemment. Vos data analysts utilisent ces méthodes sur vos données pour répondre aux questions « quoi » et « pourquoi » et planifier les prochaines étapes. \u003C/p\u003E\r\n\u003Cp\u003ELes feuilles de calcul et les versions gratuites d’outils de BI sont des ressources courantes pour analyser de petits jeux de données. Elles sont généralement utilisées par des équipes de petite taille qui n’ont parfois même pas de data analyst dédié parmi leurs collaborateurs. À l’échelle de l’entreprise, les services cloud et les frameworks de traitement de \u003Ca href=\"https://www.snowflake.com/fr/fundamentals/big-data/\"\u003EBig Data\u003C/a\u003E gèrent des jeux de données de taille intermédiaire à très grande, souvent en association avec des plateformes de BI complètes, afin de produire des visualisations et des rapports exhaustifs.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__455068363":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"how",":items":{"title_v2":{"id":"title-v2-66f33f5f47","additionalClasses":"headline-decoration","type":"heading2","lines":["Techniques d’analyse de données"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-87efd35190","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EDe manière générale, les techniques d’analyse de données sont classées en deux catégories : l’apprentissage supervisé et non supervisé. Les techniques supervisées s’appuient sur des données étiquetées pour faire des prédictions, tandis que les techniques non supervisées permettent de repérer des tendances dans des données non étiquetées.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EAnalyse de régression\u003C/h4\u003E\n\u003Cp\u003ECette technique d’apprentissage supervisé est utilisée pour prédire une valeur numérique continue d’après une ou plusieurs variables indépendantes. Autrement dit, il s’agit d’une méthode statistique qui permet de comprendre la relation entre une variable dépendante et une ou plusieurs variables indépendantes en associant une ligne ou une courbe aux données. Ainsi, elle permet de déterminer quelles variables ont un impact.\u003C/p\u003E\n\u003Cp\u003EL’\u003Ca href=\"https://hbr.org/2015/11/a-refresher-on-regression-analysis\"\u003Eanalyse de régression\u003C/a\u003E sert notamment à répondre à la question « combien » et aide les entreprises à déterminer les facteurs les plus et les moins déterminants.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EAnalyse de classification\u003C/h4\u003E\n\u003Cp\u003EL’analyse de classification permet de répondre à la question « De quelle catégorie cela relève-t-il ? ». C’est un outil efficace pour donner du sens à l’information et prendre des décisions éclairées.\u003C/p\u003E\n\u003Cp\u003ECette technique d’apprentissage supervisé est utilisée pour trier et classer les données en groupes à l’aide d’un modèle de classification entraîné pour prédire à quelle catégorie les nouvelles données qui lui sont fournies appartiennent. En substance, l’\u003Ca href=\"https://www.indicative.com/resource/classification-analysis/\"\u003Eanalyse de classification\u003C/a\u003E consiste à utiliser des données étiquetées passées pour entraîner un modèle à catégoriser correctement de nouvelles données non étiquetées.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EAnalyse en cluster\u003C/h4\u003E\n\u003Cp\u003EContrairement aux deux techniques précédentes, l’\u003Ca href=\"https://www.qualtrics.com/fr/gestion-de-l-experience/etude-marche/analyse-cluster/\"\u003Eanalyse en cluster\u003C/a\u003E est une technique d’apprentissage non supervisé utilisée pour regrouper des points de données similaires en clusters. Il n’y a pas d’étiquettes ni de catégories prédéfinies ; l’algorithme découvre les regroupements au sein des données. L’analyse en cluster permet de répondre à la question « Comment regrouper ces données ? ».\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__222865509":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"ai",":items":{"title_v2":{"id":"title-v2-b818ba962c","additionalClasses":"headline-decoration","type":"heading2","lines":["Cas d’usage de l’analyse de données"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-3c29ac1d15","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EComme nous l’avons mentionné au début de ce guide, tous les secteurs peuvent bénéficier de l’analyse de données, et les entreprises de toutes tailles s’octroient un avantage concurrentiel lorsqu’elles exploitent leurs propres données pour nourrir leurs optimisations, leur évolution et leur croissance. Examinons trois secteurs : le \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-analytics-for-retailers/\"\u003Eretail\u003C/a\u003E, la santé et les services financiers, afin de comprendre comment ceux-ci intègrent l’analyse de données dans leurs flux de travail et processus courants.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003ERetail\u003Cbr\u003E\r\n \u003C/h4\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003EPersonnalisation des publicités : les retailers peuvent exploiter les données recueillies sur leurs clients (historique des achats, données démographiques, données comportementales, etc.) pour personnaliser les promotions qu’ils leur envoient par e-mail et sur les réseaux sociaux. En effet, les expériences d’achat sur mesure favorisent la fidélité à votre marque et contribuent à augmenter votre part de portefeuille.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EGestion des stocks pour le retail en ligne : pour s’assurer que les niveaux de stock peuvent répondre à la demande, les retailers en ligne analysent l’historique des comportements d’achat des clients, les niveaux de stock, ainsi que des \u003Ca href=\"https://www.snowflake.com/fr/fundamentals/the-value-of-free-and-public-data-in-the-modern-data-economy/\"\u003Edonnées tierces et publiques\u003C/a\u003E. En évitant les ruptures de stock en ligne, vous pouvez fidéliser vos clients qui n’ont pas besoin d’aller voir ailleurs pour s’approvisionner.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003ESécurité des boutiques physiques : les boutiques physiques se doivent absolument d’éliminer tout danger pour leurs clients ou leurs collaborateurs. L’analyse d’une variété de points de données (comme les rapports d’incidents et les dossiers de formation à la sécurité) via les quatre types d’analyse de données peut aider les dirigeants à améliorer la formation à la sécurité de leurs collaborateurs, afin de réduire la fréquence des incidents.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch4\u003ESanté\u003Cbr\u003E\r\n \u003C/h4\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003EPrédiction des maladies : l’analyse prédictive s’appuie sur des données patients (mode de vie, génétique, antécédents médicaux, etc.) pour identifier les patients qui présentent un risque élevé de développer certaines pathologies. Cela aide les médecins à élaborer des plans thérapeutiques personnalisés et à commencer des soins préventifs pour anticiper les maladies.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EAffectation des ressources : les hôpitaux peuvent utiliser leurs données, comme les admissions saisonnières aux urgences, pour prévoir les niveaux d’admission de patients afin d’optimiser la gestion du personnel et du matériel. Ils peuvent ainsi répondre aux besoins de leurs patients, améliorer leur satisfaction et réduire les temps d’attente.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EDétection des fraudes : l’analyse de données peut aider les hôpitaux, les pharmacies et les compagnies d’assurance à prévenir les fraudes en analysant les schémas de facturation, l’utilisation des ordonnances et les demandes d’indemnisation, afin d’identifier les anomalies et les transactions non autorisées.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch4\u003EServices financiers\u003Cbr\u003E\r\n \u003C/h4\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003EGestion des risques : les banques peuvent analyser des données clients très variées, notamment les habitudes de dépenses, la stabilité des revenus et l’historique des paiements, afin de déterminer la solvabilité de leurs clients.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EPrédiction de la perte de clients : si certaines données (comme l’absence d’activité bancaire récente ou des frais élevés) suggèrent qu’un client risque de clôturer son compte, la banque peut proposer de manière proactive des services ou des incitations pour le conserver, comme un taux de rémunération particulier.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003ETrading algorithmique et analyse de marché : les sociétés de trading à haute fréquence utilisent des algorithmes complexes pour analyser les données du marché, identifier les opportunités et les tendances, et exécuter des transactions en quelques secondes.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__1413360324":{"columnClassNames":{"title_v2_copy":"aem-GridColumn aem-GridColumn--default--12","text_copy":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"tools",":items":{"title_v2_copy":{"id":"title-v2-342014402e","additionalClasses":"headline-decoration","type":"heading2","lines":["Outils courants d’analyse de données"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text_copy":{"id":"text-24c48c5d29","additionalClasses":"list--blue-bullets","text":"\u003Cul\u003E\r\n\u003Cli\u003EFeuilles de calcul : Microsoft Excel, Google Sheets\u003C/li\u003E\r\n\u003Cli\u003EOutils de Business Intelligence (BI) : Tableau, Microsoft Power BI\u003C/li\u003E\r\n\u003Cli\u003ELangages de programmation : \u003Ca href=\"https://www.snowflake.com/fr/fundamentals/python-for-data-engineering/\"\u003EPython\u003C/a\u003E, R, SQL\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2_copy","text_copy"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__659376865":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"conclusion",":items":{"title_v2":{"id":"title-v2-03e5b581b6","additionalClasses":"headline-decoration","type":"heading2","lines":["Conclusion"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-e636535d95","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EL’analyse de données est essentielle pour bénéficier d’un avantage concurrentiel dans pratiquement tous les secteurs. La prise de décision fondée sur les données permet de gagner en efficacité à bien des égards : optimisation des processus internes, amélioration de l’expérience client, augmentation de la fidélité à la marque, voire, dans le secteur de la santé, amélioration du bien-être des patients. \u003C/p\u003E\n\u003Cp\u003ECependant, les données continuent de croître à un rythme vertigineux. L’analyse soulève donc d’autant plus de défis complexes. Mais en parallèle, des outils et des techniques, notamment des applications d’IA avancées, offrent de nouvelles solutions pour interagir avec les données, afin d’en tirer des informations à forte valeur ajoutée. Si l’analyse de données évolue, attendez-vous à ce qu’elle reste un ingrédient clé du succès à l’ère numérique.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__1500909857":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","simple_snowflake_acc":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"faq",":items":{"title_v2":{"id":"title-v2-689fa657b8","additionalClasses":"headline-decoration","type":"heading2","lines":["FAQ sur l’analyse de données"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"simple_snowflake_acc":{"id":"simple-snowflake-accordion-947101feb0","additionalClasses":"list--blue-bullets","showDivider":false,"accordionItemsList":[{"title":"Quelles sont les meilleures formations sur l’analyse de données ?","richText":"\u003Cp\u003EChaque professionnel a un budget, une façon d’apprendre et des objectifs de carrière différents, mais les meilleures formations sur l’analyse de données vous fourniront des compétences de base solides, notamment autour des langages de programmation et des outils de visualisation de données. De nombreuses formations gratuites sont disponibles en ligne sur des plateformes comme Coursera ou DataCamp pour se familiariser avec l’analyse de données. Forbes a dressé \u003Ca href=\"https://www.forbes.com/advisor/education/certifications/best-data-analytics-certifications/\"\u003Eune liste des meilleures certifications en ligne en matière d’analyse de données\u003C/a\u003E. Snowflake propose sa \u003Ca href=\"https://learn.snowflake.com/en/certifications/snowpro-advanced-dataanalyst/?pdf_name=SnowProDataAnalystStudyGuide\"\u003Ecertification SnowPro® Advanced: Data Analyst\u003C/a\u003E pour certifier les connaissances et compétences avancées utilisées pour appliquer des principes complets d’analyse de données à l’aide de Snowflake.\u003C/p\u003E\n"},{"title":"Quels sont les outils utilisés pour l’analyse du Big Data ?","richText":"\u003Cp\u003EIl existe un certain nombre d’outils spécialisés capables de traiter rapidement d’énormes quantités de données afin d’en extraire des informations exploitables. En voici quelques exemples :\u003Cbr\u003E\n \u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003EFrameworks de Big Data : \u003Ca href=\"https://www.snowflake.com/fr/product/features/snowpark/\"\u003ESnowflake Snowpark\u003C/a\u003E, \u003Ca href=\"https://hadoop.apache.org/\"\u003EApache Hadoop\u003C/a\u003E, \u003Ca href=\"https://spark.apache.org/\"\u003EApache Spark\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003EData warehouses dans le cloud : \u003Ca href=\"https://cloud.google.com/bigquery?utm_source=google&utm_medium=cpc&utm_campaign=na-US-all-en-dr-bkws-all-all-trial-e-dr-1710134&utm_content=text-ad-none-any-DEV_c-CRE_772298885512-ADGP_Hybrid+%7C+BKWS+-+EXA+%7C+Txt-Data+Analytics-Data+Analytics-BigQuery-KWID_43700082585516178-kwd-63326440124&utm_term=KW_google%20bigquery-ST_google+bigquery&gclsrc=aw.ds&gad_source=1&gad_campaignid=22970352687&gclid=Cj0KCQjwoP_FBhDFARIsANPG24P3VZl3_a-liWj18JKg9cBt96oy0h9fSeV7h9G4GzXW5-1YxrW6tdUaAsoCEALw_wcB\"\u003EGoogle BigQuery\u003C/a\u003E, \u003Ca href=\"https://aws.amazon.com/fr/pm/redshift/?trk=a136dbb3-ff50-468b-9a66-852dc1ca985b&sc_channel=ps&ef_id=Cj0KCQjwoP_FBhDFARIsANPG24OEawaY6lV0Vnxy6v98luBjDNhrPJ71Q1KZ_r_NcuG4ZvpzRg5ZYF8aAsHOEALw_wcB:G:s&s_kwcid=AL!4422!3!651751058853!e!!g!!amazon%20redshift!19852662155!145019245577&gad_campaignid=19852662155&gbraid=0AAAAADjHtp_w47gFWrFMuAm5btwOo9ScF&gclid=Cj0KCQjwoP_FBhDFARIsANPG24OEawaY6lV0Vnxy6v98luBjDNhrPJ71Q1KZ_r_NcuG4ZvpzRg5ZYF8aAsHOEALw_wcB\"\u003EAmazon Redshift\u003C/a\u003E, \u003Ca href=\"https://www.snowflake.com/fr/product/analytics/\"\u003ESnowflake\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003EOutils de BI et de visualisation : \u003Ca href=\"https://www.tableau.com/\"\u003ETableau\u003C/a\u003E, \u003Ca href=\"https://www.microsoft.com/fr-fr/power-platform/products/power-bi\"\u003EMicrosoft Power BI\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003EBibliothèques et langages de programmation : \u003Ca href=\"https://www.python.org/\"\u003EPython\u003C/a\u003E, \u003Ca href=\"https://www.r-project.org/\"\u003ER\u003C/a\u003E, \u003Ca href=\"https://www.coursera.org/specializations/learn-sql-basics-data-science/paidmedia?utm_medium=sem&utm_source=gg&utm_campaign=b2c_namer_learn-sql-basics-data-science_ucdavis_ftcof_specializations_px_dr_bau_gg_sem_pr-bd_us-ca_en_m_hyb_24-12_x&campaignid=20743946861&adgroupid=154886907309&device=c&keyword=sql&matchtype=b&network=g&devicemodel=&creativeid=679514232408&assetgroupid=&targetid=kwd-10206160&extensionid=&placement=&gad_source=1&gad_campaignid=20743946861&gbraid=0AAAAADdKX6azVKefwfYb2NyuzsKTgMGOJ&gclid=Cj0KCQjwoP_FBhDFARIsANPG24PZTNLiGUpmlyl3WDAV8k-_Yop5rD7fxGmgImdMCl0YROUq1DUPB04aAsUhEALw_wcB\"\u003ESQL\u003C/a\u003E\u003C/li\u003E\n\u003C/ul\u003E\n"},{"title":"Comment l’analyse de données peut-elle être utilisée par exemple ?","richText":"\u003Cp\u003EPour la segmentation client dans le \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-analytics-for-retailers/\"\u003Eretail\u003C/a\u003E. \u003Ca href=\"https://www.snowflake.com/fr/solutions/industries/retail-consumer-goods/\"\u003ELes retailers\u003C/a\u003E peuvent exploiter les énormes quantités de données clients qu’ils collectent pour regrouper leurs clients en différents segments, comme ceux qui n’achètent que de l’électronique haut de gamme ou ceux qui n’achètent que pendant les soldes. Une fois les segments établis, le retailer peut ensuite envoyer du contenu marketing ciblé à chaque segment respectif, comme des recommandations de produits sur mesure ou des alertes de prévente.\u003C/p\u003E\n"},{"title":"Comment définir l’analyse de données ?","richText":"\u003Cp\u003EL’analyse de données est un domaine vaste et complet. Elle vise à comprendre le passé, afin d’en extraire des informations exploitables et d’alimenter la prise de décision fondée sur les données. Néanmoins, l’analyse de données est aussi une discipline tournée vers l’avenir, car elle sert ensuite à prévoir des comportements futurs ou encore recommander des actions. Ainsi, elle extrait des informations descriptives de données passées, puis s’appuie dessus pour créer des stratégies d’action pour l’avenir.\u003C/p\u003E\n"}],":type":"snowflake-site/components/simple-snowflake-accordion","appliedCssClassNames":"snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","simple_snowflake_acc"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__480869401":{"columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","title_v2":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"customer",":items":{"title_v2":{"id":"title-v2-05db362a8a","additionalClasses":"headline-decoration","type":"heading2","lines":["Clients Snowflake qui s’appuient sur l’analyse de données"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"flexible_column_cont":{"id":"flexible-column-container-fa0c3e595b","type":"2-column-even","alignColumns":"match-height","containerMaxWidth":"extra-large","topPadding":"extra-small","bottomPadding":"small","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-0204c65042",":items":{"card_v2":{"id":"card-v2-3db6db9568","configurationStatus":{"configured":true,"message":""},"text":{"id":"text","text":"\u003Cp\u003EVideoAmp a consolidé son data warehouse dans Snowflake pour en minimiser la complexité, réduire ses coûts et offrir de meilleurs produits à ses clients.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text"},"layoutStyle":"vertical","title":{"id":"title","type":"heading4","lines":["VideoAmp réduit ses coûts de 90 % et multiplie ses performances par 10"],":type":"snowflake-site/components/title-v2"},"button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://www.snowflake.com/en/customers/all-customers/case-study/videoamp/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Lire le témoignage"},"image":{"id":"image","alt":"simon data logo","lazyEnabled":true,"src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--ec4ca00c-4eec-44b6-a5a3-aff54ac82df4/videoamp-customer-card%25402x.jpg?quality=85&preferwebp=true","height":"720","width":"1680",":type":"snowflake-site/components/image"},"type":"content-card",":type":"snowflake-site/components/card-v2"}},":itemsOrder":["card_v2"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"container-76e16a083f",":items":{"card_v2_copy":{"id":"card-v2-f2befd7c9a","configurationStatus":{"configured":true,"message":""},"text":{"id":"text","text":"\u003Cp\u003EGrâce à Snowflake, Luminate, qui alimente les célèbres palmarès musicaux Billboard et représente le partenaire de données le plus fiable du secteur du divertissement, a unifié ses données pour développer des produits plus innovants et optimiser le traitement des données.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text"},"layoutStyle":"vertical","title":{"id":"title","type":"heading4","lines":["Luminate optimise l’analytique dans le divertissement avec un traitement des données 300 % plus rapide et des informations plus riches"],":type":"snowflake-site/components/title-v2"},"button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/customers/all-customers/case-study/luminate/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Lire le témoignage"},"image":{"id":"image","alt":"penske logo","lazyEnabled":true,"src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--d9737759-71b7-405c-a577-db0a59c6677a/luminate-customer-card%25402x.jpg?quality=85&preferwebp=true","height":"720","width":"1680",":type":"snowflake-site/components/image"},"type":"content-card",":type":"snowflake-site/components/card-v2"}},":itemsOrder":["card_v2_copy"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"isBlogPage":false,"isActiveTOC":false,":type":"snowflake-site/components/flexible-column-container"}},":itemsOrder":["title_v2","flexible_column_cont"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__373061683":{"columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","title_v2":"aem-GridColumn 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