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18.5613C5.83407 18.8998 6.35311 18.9224 6.68033 18.629L11.9159 13.9464L12.9201 15.0409C13.8454 16.0564 15.0865 16.6093 16.418 16.6093C17.7495 16.6093 18.9906 16.0564 19.9159 15.0409L20.8637 14.0028L26.0428 18.6516H26.0654C26.4039 18.945 26.9117 18.9111 27.205 18.5726C27.4984 18.2341 27.4645 17.7264 27.126 17.433L21.9695 12.818L27.7466 6.49927Z\" fill=\"#249EDC\"/\u003E\r\n\u003C/svg\u003E\u003C/span\u003E\r\n\u003C/div\u003E","cssContent":".share-icon__svg *{pointer-events:none}.share-icon-group{display:flex;gap:24px;align-items:center}.share-icon{display:inline-block}.share-icon svg{height:32px}.share-icon__svg:hover path{fill:var(--ui-02);transition:300ms ease fill}.share-icon__svg path{transition:300ms ease fill}","jsContent":"const pageURL = window.location.href;\r\n\r\ndocument.addEventListener('click', (e) =\u003E {\r\n\r\nconst targetClassesArr = [...e.target.classList];\r\nconsole.log(targetClassesArr);\r\nif (targetClassesArr.includes('share-icon--linkedin')) {\r\nconst shareURL = `https://www.linkedin.com/sharing/share-offsite/?url=${pageURL}`;\r\nwindow.open(shareURL, '_blank');\r\n}\r\nif (targetClassesArr.includes('share-icon--facebook')) {\r\nconst shareURL = `http://www.facebook.com/sharer/sharer.php?u=${pageURL}`;\r\nwindow.open(shareURL, '_blank');\r\n}\r\nif (targetClassesArr.includes('share-icon--twitter')) {\r\nconst shareURL = `https://twitter.com/intent/tweet?url=${pageURL}`;\r\nwindow.open(shareURL, '_blank');\r\n}\r\nif (targetClassesArr.includes('share-icon--email')) {\r\nconst shareURL = `mailto:?subject=Check out this news from Snowflake&body=${pageURL}`;\r\nwindow.open(shareURL);\r\n}\r\n\r\n\r\n\r\n\r\n\r\n});",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false}},":itemsOrder":["markup_editor"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small"}},":itemsOrder":["container_949147658"]},"cq:LiveSyncConfig":{"cq:isDeep":true,"cq:rolloutConfigs":[],"cq:master":"/content/experience-fragments/snowflake-site/language-masters/fr/site/share-icons/share-icons",":type":"cq:LiveCopy"}},":itemsOrder":["root","cq:LiveSyncConfig"],"appliedCssClassNames":"snowflake-responsive-component-top-padding-extra-small"}},":itemsOrder":["text","experiencefragment"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"fundamentals-main-content",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"container_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":"overview",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-4d58e42b3e","additionalClasses":"headline-decoration","type":"heading2","lines":["Présentation"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-8ea0e95a61","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003ELes entreprises ne peuvent pas s’appuyer uniquement sur des données en temps réel pour prendre des décisions éclairées. Elles doivent comprendre les subtilités de leur activité et utiliser des informations actuelles pour planifier l’avenir. De plus, elles doivent étudier leurs performances passées pour anticiper leurs résultats futurs. C’est là qu’entre en jeu l’analyse prédictive.\u003C/p\u003E\r\n\u003Cp\u003EL’analyse prédictive est une sous-discipline de \u003Ca href=\"https://www.snowflake.com/fr/fundamentals/data-analytics/\"\u003El’analyse de données\u003C/a\u003E. Axée sur la \u003Ca href=\"https://www.snowflake.com/fr/customers/all-customers/case-study/igs-energy/\"\u003Eprévision\u003C/a\u003E, l’atténuation des risques et la création de parcours clients personnalisés plus éclairés, elle constitue pour les entreprises un élément clé de la planification stratégique globale. \u003C/p\u003E\r\n\u003Cp\u003EDans cet article, nous nous intéressons aux subtilités de l’analyse prédictive et à son fonctionnement. Nous expliquons également comment elle peut avoir un impact positif pour les entreprises quand elle est utilisée efficacement, quels que soient les secteurs d’activité et les fonctions stratégiques.\u003C/p\u003E\r\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"},"container_copy_copy_":{"columnClassNames":{"container":"aem-GridColumn aem-GridColumn--default--12","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",":type":"snowflake-site/components/container",":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",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-4d7c1af1da","additionalClasses":"headline-decoration","type":"heading2","lines":["Qu’est-ce que l’analyse prédictive ?"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-e528b0b0af","text":"\u003Cp\u003EL’analyse prédictive s’appuie sur des données historiques pour élaborer des scénarios potentiels probables, anticiper des tendances futures et prendre des décisions stratégiques véritablement éclairées. Ainsi, elle aide les entreprises à avoir une vision plus éclairée de leurs résultats futurs estimés. \u003C/p\u003E\r\n\u003Cp\u003EL’analyse prédictive est l’une des composantes de l’analyse de données, une discipline plus large qui comporte trois autres parties : l’analyse descriptive, diagnostique et prescriptive. L’analyse prédictive se concentre sur ce qui pourrait se produire dans l’avenir. En revanche, l’analyse descriptive se concentre sur ce qui s’est réellement passé, l’analyse diagnostique cherche à expliquer pourquoi et l’analyse prescriptive s’efforce de déterminer ce qu’il faut faire ensuite. \u003C/p\u003E\r\n\u003Cp\u003EÀ l’aide de données historiques, l’analyse prédictive s’appuie à la fois sur des processus manuels et sur des \u003Ca href=\"https://www.snowflake.com/fr/product/ai/\"\u003Eoutils d’IA et de machine learning\u003C/a\u003E pour élaborer des hypothèses futures. Au cœur de ses principes se trouvent de multiples outils statistiques, tels que le machine learning, la modélisation prédictive ou encore le \u003Ca href=\"https://www.snowflake.com/fr/fundamentals/data-mining/\"\u003Edata mining\u003C/a\u003E.\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"},"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",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-066b598b2d","additionalClasses":"headline-decoration","type":"heading2","lines":["Comment fonctionne l’analyse prédictive ?"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-e1f4be113d","text":"\u003Cp\u003EL’analyse prédictive permet aux entreprises d’avoir une vision plus éclairée de la suite des événements. Elle a pour fonction de transformer des données historiques d’une entreprise concernant ses \u003Ca href=\"https://www.snowflake.com/fr/solutions/departments/finance/\"\u003Efinances\u003C/a\u003E, le comportement de ses clients et plus encore en projections prévisionnelles.\u003C/p\u003E\n\u003Cp\u003EVoici les composants clés nécessaires pour vous lancer dans la modélisation de l’analyse prédictive : tout d’abord, définissez le problème que vous cherchez à résoudre ; ensuite, collectez les données pertinentes associées à ce problème ; , enfin, organisez ces données de manière significative et instructive. À partir de là, les entreprises peuvent développer des modèles prédictifs pour obtenir des informations éclairées sur ce qui va probablement se produire par la suite. \u003C/p\u003E\n\u003Cp\u003EPour ce faire, les data scientists utilisent des modèles pour identifier des corrélations entre les multiples points de données d’un jeu de données. Grâce à l’IA, au ML, au data mining et aux statistiques, ils recherchent des schémas déjà vus par le passé et évaluent la probabilité que ces mêmes événements se reproduisent à l’avenir. Ils en tirent des conclusions sur les variables les plus susceptibles d’affecter les résultats de l’entreprise et génèrent les prédictions les plus probables à partir de là.\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"},"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",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-7a4029474e","additionalClasses":"headline-decoration","type":"heading2","lines":["Types de modèles d’analyse prédictive"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-50cbb90de7","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EIl existe cinq principaux types de modèles ou de méthodes qui relèvent de l’analyse prédictive : les modèles de classification, les modèles de clustering, les \u003Ca href=\"https://www.snowflake.com/fr/fundamentals/time-series-analysis/\"\u003Emodèles de séries temporelles\u003C/a\u003E, les modèles de régression et les méthodes d’ensemble. Voici les caractéristiques de chacun. \u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003EModèles de classification\u003C/h4\u003E\r\n\u003Cp\u003ECes modèles catégorisent les données en fonction d’informations historiques et permettent de décrire les relations au sein d’un jeu de données. À l’aide du machine learning, un modèle de classification apprend la relation entre les données et leurs libellés, afin de classer les nouvelles données au fur et à mesure de leur ajout. \u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003EModèles de clustering\u003C/h4\u003E\r\n\u003Cp\u003ECes modèles regroupent les points de données qui présentent des caractéristiques similaires. Grâce à une matrice de données, ils connectent des points de données similaires et identifient des schémas que d’autres techniques de modélisation peinent parfois à mettre en évidence. \u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003EModèles de séries temporelles\u003C/h4\u003E\r\n\u003Cp\u003ECes modèles utilisent des points de données capturés sur une période définie, qu’elle soit quotidienne, hebdomadaire, mensuelle ou annuelle. Ce type de modélisation est la forme d’analyse prédictive la plus couramment utilisée. Il évalue les changements saisonniers, les comportements cycliques des clients et les tendances au fil du temps. \u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003EModèles de régression\u003C/h4\u003E\r\n\u003Cp\u003ECes modèles décryptent la relation entre deux variables sur une période donnée. Par exemple, ils peuvent examiner des données clients et prédire le chiffre d’affaires que chaque client rapportera tout au long de son cycle de vie. Ces modèles montrent comment des actions spécifiques peuvent avoir un impact sur les résultats globaux d’une entreprise. \u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003EMéthodes d’ensemble \u003C/h4\u003E\r\n\u003Cp\u003ELes méthodes d’ensemble permettent de rassembler tous ces modèles afin de créer un ensemble d’informations plus exhaustif et instructif. Cela permet de comprendre les données dans toute leur complexité et d’en tirer des informations plus unifiées, afin d’aider les cadres dirigeants à prendre des décisions. \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"},"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",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-b818f628ca","additionalClasses":"headline-decoration","type":"heading2","lines":["Pourquoi utiliser l’analyse prédictive ?"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-e159d962cd","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EL’analyse prédictive peut aider les entreprises à mieux comprendre leurs activités et à obtenir des informations pertinentes pour aller de l’avant. Les entreprises peuvent étudier des tendances dans leurs données afin de prévoir leurs performances futures et ainsi prendre de meilleures décisions. \u003C/p\u003E\r\n\u003Cp\u003EGrâce à l’analyse prédictive, les entreprises peuvent également améliorer l’expérience client en développant des parcours personnalisés qui répondent mieux aux besoins de leurs clients. En outre, l’analyse prédictive permet de \u003Ca href=\"https://www.snowflake.com/fr/fundamentals/ai-governance-threat-intelligence-and-ml-anomaly-detection/\"\u003Edétecter des anomalies\u003C/a\u003E, telles que des schémas qui trahissent des fraudes, afin d’y remédier avant qu’elles ne dégénèrent. \u003C/p\u003E\r\n\u003Cp\u003EDe manière générale, les entreprises peuvent ainsi améliorer leur efficacité opérationnelle. Grâce à l’analyse prédictive, les entreprises peuvent se baser sur les performances passées plutôt que sur des suppositions pour déterminer quels types de campagne ou de programme lancer.\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"},"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",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-e93b61b19e","additionalClasses":"headline-decoration","type":"heading2","lines":["Techniques d’analyse prédictive"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-7dd90cec0e","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EIl existe quelques techniques d’analyse prédictive couramment utilisées, que nous décryptons ci-dessous.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EAnalyse de régression\u003C/h4\u003E\n\u003Cp\u003ECette forme d’analyse s’efforce de prédire la relation entre des variables. Elle est appliquée dans des jeux de données pour trouver des tendances et des corrélations entre des points de données. Une formule ainsi créée dans un jeu de données permet de suivre une telle corrélation. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EArbres de décision\u003C/h4\u003E\n\u003Cp\u003ECette technique permet de cartographier une série de décisions prises en classant les données dans diverses catégories en fonction de variables. Elle peut être utilisée pour lister les divers résultats que pourraient donner différents choix. Comme ces modèles sont faciles à examiner et à comprendre, ils peuvent contribuer à accélérer la prise de décision. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003ERéseaux neuronaux\u003C/h4\u003E\n\u003Cp\u003ECette technique a été créée pour identifier des relations non linéaires au sein de jeux de données. Grâce à l’IA et à des outils de reconnaissance de schémas, un réseau neuronal imite le fonctionnement de l’esprit humain pour établir des associations entre des points de données apparemment sans rapport. Il peut analyser plusieurs formes de données, notamment du texte, des images, de l’audio, etc. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EPrévision de séries temporelles\u003C/h4\u003E\n\u003Cp\u003ELa prévision de séries temporelles est une technique essentielle, car les entreprises s’intéressent souvent à des points de données sur une période définie. Ce type de prévision se concentre sur des itérations quotidiennes, hebdomadaires ou mensuelles des données. Il se concentre sur des tendances comportementales au fil du temps pour prédire des résultats. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EAlgorithmes de clustering\u003C/h4\u003E\n\u003Cp\u003ELe clustering connecte des points de données similaires. Grâce au clustering, les entreprises peuvent utiliser des données, comme un achat passé, pour prédire le produit qu’un client est susceptible d’acheter ensuite.\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"},"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",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-f98fd20f7a","additionalClasses":"headline-decoration","type":"heading2","lines":["Cas d’usage de l’analyse prédictive"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-6c3df270e5","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EDans tous les secteurs d’activité et pour toutes les fonctions d’une entreprise, l’analyse prédictive peut représenter un atout. Nous détaillons ci-dessous quelques cas d’usage courants dans les principaux secteurs. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EServices financiers\u003C/h4\u003E\n\u003Cp\u003EEn étudiant les antécédents de crédit d’un client, une \u003Ca href=\"https://www.snowflake.com/fr/solutions/industries/financial-services/\"\u003Esociété financière\u003C/a\u003E peut être plus à même de prédire la probabilité qu’un client rembourse un prêt. L’analyse prédictive peut également contribuer à \u003Ca href=\"https://www.snowflake.com/en/solutions/industries/financial-services/fraud-detection-and-financial-crimes/\"\u003Elutter contre la fraude\u003C/a\u003E. En effet, les institutions financières peuvent repérer les irrégularités dans les transactions, signaler leurs inquiétudes en temps réel et mettre en place des garde-fous.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003ESanté \u003C/h4\u003E\n\u003Cp\u003EL’analyse prédictive peut avoir un impact significatif sur les patients. Les \u003Ca href=\"https://www.snowflake.com/fr/solutions/industries/healthcare-and-life-sciences/\"\u003Eorganisations de santé\u003C/a\u003E peuvent s’appuyer sur des analyses pour \u003Ca href=\"https://www.snowflake.com/en/solutions/industries/healthcare-and-life-sciences/care-delivery/\"\u003Egérer les soins\u003C/a\u003E en suivant des points de données qui signalent le début d’un problème plus grave, comme une septicémie chez des patients hospitalisés pour des soins de longue durée. Ces organisations peuvent également examiner les dossiers médicaux de leurs patients afin de leur proposer un traitement préventif, par exemple en recommandant un régime adapté à un patient qui présente des antécédents familiaux de diabète. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EMarketing\u003C/h4\u003E\n\u003Cp\u003EL’analyse prédictive peut \u003Ca href=\"https://www.snowflake.com/en/fundamentals/predictive-analytics-marketing/\"\u003Eévaluer le succès de futures campagnes marketing\u003C/a\u003E avec plus de précision. Ainsi, les \u003Ca href=\"https://www.snowflake.com/fr/solutions/departments/marketing/\"\u003Espécialistes du marketing\u003C/a\u003E peuvent s’appuyer sur des données historiques pour déterminer les types de campagnes avec lesquelles leurs audiences cibles interagissent et ajuster leurs stratégies en fonction des besoins. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003ESupply chain \u003C/h4\u003E\n\u003Cp\u003EL’analyse prédictive peut aider les \u003Ca href=\"https://www.snowflake.com/fr/solutions/industries/manufacturing/\"\u003Eindustriels\u003C/a\u003E à mieux gérer et répartir leurs stocks. Grâce à des données historiques, les fournisseurs peuvent anticiper les besoins de tel ou tel client en approvisionnement, de façon à mieux gérer leurs propres stocks. Ils peuvent également suggérer de manière proactive à leurs clients de repasser commande en fonction des données historiques sur leurs besoins et leurs demandes.\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"},"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",":type":"snowflake-site/components/container",":items":{"title_v2_copy":{"id":"title-v2-c31cc8339a","additionalClasses":"headline-decoration","type":"heading2","lines":["Avantages de l’analyse prédictive pour la réussite des entreprises"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text_copy":{"id":"text-68b0521e10","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003ELes entreprises peuvent tirer de nombreux avantages de l’analyse prédictive. Les principaux avantages sont les suivants :\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E1. Planification et prévisions améliorées\u003C/h4\u003E\n\u003Cp\u003EPour rester compétitives, les entreprises doivent anticiper l’avenir en prédisant leurs résultats, en saisissant des opportunités et en se protégeant des pertes potentielles. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E2. Meilleur ciblage et fidélisation des clients\u003C/h4\u003E\n\u003Cp\u003EGrâce à l’analyse prédictive, les cadres dirigeants peuvent cerner les comportements de leurs clients. Ainsi, les entreprises qui analysent leur clientèle et appliquent l’analyse prédictive à leurs profils clients peuvent adapter leurs campagnes marketing à des audiences spécifiques et obtenir des informations plus pertinentes sur les meilleures probabilités d’engagement. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E3. Réduction du risque opérationnel\u003C/h4\u003E\n\u003Cp\u003EAvec l’analyse prédictive, les entreprises peuvent améliorer la détection des fraudes et la gestion des risques financiers. Les entreprises peuvent signaler plus tôt les achats douteux ou anormaux qui sortent du cadre habituel. En outre, les entreprises peuvent examiner plus facilement des points de données tels que des scores de crédit ou des demandes d’indemnisation pour prédire le risque de défaut de paiement associé à un client. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E4. Augmentation du ROI et de l’efficacité\u003C/h4\u003E\n\u003Cp\u003EDe manière générale, l’analyse prédictive peut améliorer l’efficacité et le retour sur investissement d’une entreprise. En effet, elle aide les entreprises à prévoir leurs stocks et à mieux gérer leurs ressources internes. Elle les aide également à prédire les performances d’un produit en développement en examinant les données sur les besoins et les envies de leurs clients. Les entreprises peuvent également s’en servir pour éviter les retards de production en surveillant la maintenance de routine de leurs équipements. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E5. Meilleure prise de décision grâce à des informations basées sur des données \u003C/h4\u003E\n\u003Cp\u003EGrâce à l’analyse prédictive, les entreprises disposent de plus d’informations pour prendre de meilleures décisions. Ainsi, elles peuvent agir de manière proactive en examinant des tendances historiques pour faciliter la prise de décision pour l’avenir, que ce soit concernant la quantité d’un certain produit à garder en stock, les types de campagnes marketing à développer ou encore des solutions pour améliorer la productivité de leurs opérations.\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_copy","text_copy"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small"},"container":{"columnClassNames":{"text_copy_copy":"aem-GridColumn aem-GridColumn--default--12","title_v2_copy_copy":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"starting",":type":"snowflake-site/components/container",":items":{"title_v2_copy_copy":{"id":"title-v2-b1d338bbde","additionalClasses":"headline-decoration","type":"heading2","lines":["Premiers pas avec l’analyse prédictive"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text_copy_copy":{"id":"text-eea2322aef","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EIntroduire l’analyse prédictive en tant qu’élément essentiel de votre activité peut sembler une tâche colossale. Vous trouverez ci-dessous les étapes clés pour vous lancer. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E1. Identifier un problème stratégique clair\u003C/h4\u003E\n\u003Cp\u003ETout d’abord, identifiez clairement votre objectif avant de commencer à utiliser l’analyse prédictive. À quelle question voulez-vous répondre ? Quelles sont les principales priorités de votre entreprise ? Créez une liste de questions pour vous aider à aller à la racine de votre problème. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E2. Créer une équipe transversale \u003C/h4\u003E\n\u003Cp\u003EAssurez-vous de l’alignement de votre équipe. Mettez en place des canaux de communication et des plans d’action et faites le point régulièrement avec les différentes fonctions stratégiques qui peuvent bénéficier des prédictions et les exploiter. Les informations ne valent rien si elles ne permettent pas de passer à l’action. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E3. Choisir des données et des outils accessibles\u003C/h4\u003E\n\u003Cp\u003EVous avez besoin de technologies efficaces pour stocker et analyser vos données. Pour assurer la transparence et la rapidité du reporting, il est utile de disposer d’outils accessibles aux collaborateurs de toutes les fonctions stratégiques jusqu’à la direction. Si vos collaborateurs non techniques peuvent utiliser ces outils et leur poser des questions pertinentes, cela élimine la nécessité de faire appel à une équipe de data science pour exécuter des requêtes, au profit de l’efficacité de l’analyse prédictive. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E4. Commencer par un petit projet pilote\u003C/h4\u003E\n\u003Cp\u003ECommencez par un petit projet pilote tout simple pour faciliter votre parcours avant de mettre en œuvre des projets d’analyse prédictive plus vastes. Lancez-vous sur un petit problème qui nécessite un jeu de données restreint pour montrer l’impact stratégique de base de l’analyse prédictive. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E5. Mesurer le ROI et avancer progressivement \u003C/h4\u003E\n\u003Cp\u003ECommencez par des projets bien définis et mesurables et calculez le retour sur investissement avant de développer le projet ou d’en lancer d’autres pour d’autres fonctions stratégiques. Au fur et à mesure de vos avancées, vous pouvez connecter l’analyse prédictive entre plusieurs fonctions pour automatiser davantage vos flux de travail et améliorer son ROI. \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_copy_copy","text_copy_copy"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small"},"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",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-ecf6e94e7c","additionalClasses":"headline-decoration","type":"heading2","lines":["Conclusion"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-534bebf0dc","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EL’analyse prédictive est essentielle pour toute entreprise qui cherche à prendre des décisions éclairées basées sur des données historiques. En examinant les tendances associées aux performances passées, les entreprises peuvent adapter leurs stratégies pour prendre des décisions plus éclairées et, avec un peu de chance, obtenir de meilleurs résultats.\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"},"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",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-01511125a4","additionalClasses":"headline-decoration","type":"heading2","lines":["Questions fréquentes sur l’analyse prédictive"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"simple_snowflake_acc":{"id":"simple-snowflake-accordion-ed03ac9ebd","additionalClasses":"list--blue-bullets","showDivider":false,"accordionItemsList":[{"title":"Quels outils d’analyse prédictive existe-t-il ?","richText":"\u003Cp\u003ELes outils d’analyse prédictive incluent des plateformes complètes qui prennent en charge la préparation des données et la construction de modèles. Ils incluent également des plateformes low-code qui offrent des flux de travail visuels pour la création de modèles. Les utilisateurs moins expérimentés en codage utilisent généralement ces outils. En outre, il existe des outils open source plus flexibles pour les utilisateurs avancés. \u003C/p\u003E\n"},{"title":"ChatGPT est-il un modèle prédictif ?","richText":"\u003Cp\u003ELes \u003Ca href=\"https://www.snowflake.com/fr/fundamentals/large-language-model/\"\u003ELLM\u003C/a\u003E (comme ChatGPT) créent des réponses en langage naturel qui imitent le discours humain en prédisant le mot suivant le plus probable d’une série. Les LLM peuvent aider à la préparation des données et à d’autres tâches impliquées dans l’analyse prédictive. Au prix d’un petit effort, il est même possible de leur demander d’effectuer une analyse prédictive sur des données que vous chargez. ChatGPT peut traiter de grandes quantités de données assez rapidement, identifier des tendances clés et prévoir des résultats potentiels si l’utilisateur le lui demande. \u003C/p\u003E\n"},{"title":"Quelle est la différence entre l’analyse prédictive et le machine learning ?","richText":"\u003Cp\u003ELe machine learning est un outil utilisé pour soutenir l’analyse prédictive. Le machine learning permet d’identifier des tendances au sein de données, qui permettent ensuite d’obtenir des informations éclairées à l’aide de l’analyse prédictive. \u003C/p\u003E\n"},{"title":"Les outils d’analyse prédictive sont-ils précis ?","richText":"\u003Cp\u003EL’analyse prédictive ne fait rien d’autre que des prédictions. Elle s’appuie sur les points de données pertinents collectés. Si elle peut aider les entreprises à prendre des décisions plus éclairées, elle ne constitue qu’une pièce du puzzle. Plus les données sont de qualité et plus les questions posées sont pertinentes, plus les prédictions qui en résultent sont susceptibles d’être fiables.\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"},"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",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-f46d7d6b35","additionalClasses":"headline-decoration","type":"heading2","lines":["Clients qui utilisent Snowflake"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"flexible_column_cont":{"id":"flexible-column-container-f9219f999c","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-f206131317",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"card_v2":{"id":"card-v2-1f1042117f","configurationStatus":{"configured":true,"message":""},":type":"snowflake-site/components/card-v2","type":"content-card","image":{"id":"image","lazyEnabled":true,"src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--3c22294a-3e45-4a55-aa6d-f48810873b7e/whoop-customer-card%25402x.jpg?preferwebp=true&quality=85","height":"720","alt":"simon data logo","width":"1680",":type":"snowflake-site/components/image"},"text":{"id":"text","text":"\u003Cp\u003EGrâce à Snowflake et Apache Iceberg, les équipes de WHOOP centralisent l’accès aux données tout en réduisant la complexité, en réduisant les coûts et en améliorant des processus stratégiques.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text"},"layoutStyle":"vertical","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://www.snowflake.com/en/customers/all-customers/case-study/whoop/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Lire le témoignage"},"title":{"id":"title","type":"heading4","lines":["WHOOP améliore les prévisions financières en matière d’IA et de ML tout en améliorant l’expérience de ses membres"],":type":"snowflake-site/components/title-v2"}}},":itemsOrder":["card_v2"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"container-d703082b47",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"card_v2_copy":{"id":"card-v2-dbde5370b4","configurationStatus":{"configured":true,"message":""},":type":"snowflake-site/components/card-v2","type":"content-card","image":{"id":"image","lazyEnabled":true,"src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--bd040113-0d19-45d5-be25-21e8fbcff330/gilbert-customer-card%25402x.jpg?preferwebp=true&quality=85","height":"720","alt":"penske logo","width":"1680",":type":"snowflake-site/components/image"},"text":{"id":"text","text":"\u003Cp\u003ELes analytics engineers de Canva expliquent comment Snowflake change la donne et évolue au rythme de la croissance de leur entreprise. Canva utilise Snowpipe pour ingérer des données à des fins d’analyse prédictive et exploite le data mesh pour bénéficier de son évolutivité à l’échelle de l’entreprise.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text"},"layoutStyle":"vertical","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://www.snowflake.com/en/customers/all-customers/video/canva-1/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Regarder la vidéo"},"title":{"id":"title","type":"heading4","lines":["Canva améliore ses interactions avec ses clients grâce à Snowflake"],":type":"snowflake-site/components/title-v2"}}},":itemsOrder":["card_v2_copy"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium"},":type":"snowflake-site/components/flexible-column-container","isActiveTOC":false,"isBlogPage":false}},":itemsOrder":["title_v2","flexible_column_cont"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small"},"container_copy_copy__373061683":{"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":"resources",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-a4dc801a60","type":"heading2","lines":["Ressources sur 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