{"id":255056,"date":"2024-11-01T06:30:00","date_gmt":"2024-11-01T06:30:00","guid":{"rendered":"https:\/\/datascientest.com\/?p=255056"},"modified":"2024-11-19T11:43:18","modified_gmt":"2024-11-19T11:43:18","slug":"tables-de-dimensions-data-warehouse","status":"publish","type":"post","link":"https:\/\/datascientest.com\/tables-de-dimensions-data-warehouse","title":{"rendered":"Les tables de dimensions dans un Data Warehouse"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"255056\" class=\"elementor elementor-255056\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-56a33a3 e-flex e-con-boxed e-con\" data-id=\"56a33a3\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5bbf9df elementor-widget elementor-widget-text-editor\" data-id=\"5bbf9df\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><strong>En data science et plus pr\u00e9cis\u00e9ment dans les data warehouses, les termes dimension table (table de dimension) et facts table (table de faits) sont des concepts cl\u00e9s dans tout mod\u00e8le de donn\u00e9es, entre autres, \u00e0 des fins d&rsquo;analyse.<\/strong><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-11384ca e-flex e-con-boxed e-con\" data-id=\"11384ca\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-c3f662a e-con-full e-flex e-con\" data-id=\"c3f662a\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-cabd543 elementor-widget elementor-widget-image\" data-id=\"cabd543\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"512\" height=\"512\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image3.webp\" class=\"attachment-large size-large wp-image-255089\" alt=\"\" loading=\"lazy\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image3.webp 512w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image3-300x300.webp 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image3-150x150.webp 150w\" sizes=\"(max-width: 512px) 100vw, 512px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-f7753c4 e-con-full e-flex e-con\" data-id=\"f7753c4\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4e7cda8 elementor-widget elementor-widget-heading\" data-id=\"4e7cda8\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h3 class=\"elementor-heading-title elementor-size-default\">Rappel : qu'est-ce qu'un data warehouse ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ce68306 elementor-widget elementor-widget-text-editor\" data-id=\"ce68306\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/datascientest.com\/data-warehouse\">Un data warehouse est une plateforme centralis\u00e9e de stockage de donn\u00e9es<\/a>, con\u00e7ue pour faciliter l&rsquo;analyse et la prise de d\u00e9cision. Il regroupe des donn\u00e9es provenant de diff\u00e9rentes sources et les organise de mani\u00e8re \u00e0 permettre des analyses rapides et efficaces. Contrairement aux bases de donn\u00e9es op\u00e9rationnelles, un data warehouse est optimis\u00e9 pour <strong>l&rsquo;analyse des donn\u00e9es historiques<\/strong>, offrant ainsi une meilleure vision des performances pass\u00e9es et pr\u00e9sentes.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-bb76e10 e-flex e-con-boxed e-con\" data-id=\"bb76e10\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ee239f0 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"ee239f0\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formations-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Approfondir sur le data warehousing<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-566033c e-flex e-con-boxed e-con\" data-id=\"566033c\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f78a501 elementor-widget elementor-widget-heading\" data-id=\"f78a501\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Qu'est-ce qu'une table de dimension ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c01b0f1 elementor-widget elementor-widget-text-editor\" data-id=\"c01b0f1\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><b>Une dimension est une table qui stocke des attributs qualitatifs<\/b><span style=\"font-weight: 400;\"> d&rsquo;un \u00e9l\u00e9ment cl\u00e9 du processus de l&rsquo;entreprise. Ces attributs sont utilis\u00e9s pour d\u00e9crire <\/span><b>les faits num\u00e9riques<\/b><span style=\"font-weight: 400;\">, qui sont \u00e0 leur tour enregistr\u00e9s dans les tables de faits.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Les dimensions permettent donc de fournir un contexte aux mesures quantitatives. Elles donnent des d\u00e9tails sur les \u00e9v\u00e9nements, par exemple, qui, quand, o\u00f9, ou \u00e0 quel produit une vente a \u00e9t\u00e9 r\u00e9alis\u00e9e.<\/span><\/p><p><span style=\"font-weight: 400;\">Ces attributs peuvent inclure des \u00e9l\u00e9ments tels que le produit, la date, le client, ou m\u00eame le lieu. Ces tables sont organis\u00e9es de mani\u00e8re \u00e0 rendre l\u2019analyse des donn\u00e9es plus intuitive, facilitant ainsi la compr\u00e9hension des <\/span><b>tables de faits, qui contiennent quant \u00e0 elle les mesures quantitatives.<\/b><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-0d83b2f e-flex e-con-boxed e-con\" data-id=\"0d83b2f\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-33b12dd elementor-widget elementor-widget-heading\" data-id=\"33b12dd\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Les types de sch\u00e9mas utilis\u00e9s<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f17a960 elementor-widget elementor-widget-text-editor\" data-id=\"f17a960\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Il existe plusieurs mod\u00e8les permettant d\u2019organiser les tables de faits et de dimensions, notamment les mod\u00e8les en \u00e9toile (<\/span><b>star schema<\/b><span style=\"font-weight: 400;\">) et en flocon de neige (<\/span><b>snowflake schema<\/b><span style=\"font-weight: 400;\">).<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-e2fbcb1 e-flex e-con-boxed e-con\" data-id=\"e2fbcb1\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-5776c28 e-con-full e-flex e-con\" data-id=\"5776c28\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-fdb654d elementor-widget elementor-widget-image\" data-id=\"fdb654d\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"848\" height=\"579\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image5.webp\" class=\"attachment-full size-full wp-image-255075\" alt=\"\" loading=\"lazy\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image5.webp 848w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image5-300x205.webp 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image5-768x524.webp 768w\" sizes=\"(max-width: 848px) 100vw, 848px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-164b634 e-con-full e-flex e-con\" data-id=\"164b634\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-26cdb69 elementor-widget elementor-widget-heading\" data-id=\"26cdb69\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-medium\">Star Schema<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cffa8a7 elementor-widget elementor-widget-text-editor\" data-id=\"cffa8a7\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Ce type de sch\u00e9ma est le plus simple et le plus couramment utilis\u00e9 en data warehousing. Ici, les tables de faits sont plac\u00e9es au centre et sont reli\u00e9es aux tables de dimensions qui l&rsquo;entourent, formant une structure en forme d&rsquo;\u00e9toile. Cela facilite l&rsquo;analyse des donn\u00e9es car les relations entre tables sont claires et peu complexes. Il est g\u00e9n\u00e9ralement l&rsquo;approche conseill\u00e9e dans la mesure du possible.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-152d5ec e-flex e-con-boxed e-con\" data-id=\"152d5ec\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-4b41e25 e-con-full e-flex e-con\" data-id=\"4b41e25\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4a46279 elementor-widget elementor-widget-image\" data-id=\"4a46279\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1200\" height=\"725\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image2.webp\" class=\"attachment-full size-full wp-image-255082\" alt=\"\" loading=\"lazy\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image2.webp 1200w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image2-300x181.webp 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image2-1024x619.webp 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image2-768x464.webp 768w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-d881010 e-con-full e-flex e-con\" data-id=\"d881010\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9e3bfe4 elementor-widget elementor-widget-heading\" data-id=\"9e3bfe4\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-medium\">Snowflake Schema<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-43332ad elementor-widget elementor-widget-text-editor\" data-id=\"43332ad\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Le sch\u00e9ma en flocon de neige est une extension du star schema, dans lequel les tables de dimensions sont normalis\u00e9es \u00e0 plusieurs niveaux. Cela signifie que les attributs d\u2019une dimension sont \u00e0 leur tour reli\u00e9s \u00e0 d&rsquo;autres tables, formant une structure plus complexe qui ressemble \u00e0 un flocon de neige. Cela permet de r\u00e9duire la redondance des donn\u00e9es, mais augmente la complexit\u00e9 des requ\u00eates.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-e805b53 e-flex e-con-boxed e-con\" data-id=\"e805b53\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ab10908 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"ab10908\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formations-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Se former au data warehousing<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-de950a2 e-flex e-con-boxed e-con\" data-id=\"de950a2\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-8c07a15 elementor-widget elementor-widget-heading\" data-id=\"8c07a15\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Primary Keys et Foreign Keys<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d793dff elementor-widget elementor-widget-text-editor\" data-id=\"d793dff\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Dans un mod\u00e8le dimensionnel, les tables de dimensions disposent d&rsquo;une<\/span><b> cl\u00e9 primaire<\/b><span style=\"font-weight: 400;\"> (primary key) <\/span><b>qui identifie de mani\u00e8re unique chaque ligne<\/b><span style=\"font-weight: 400;\">. Cette primary key est \u00e0 son tour utilis\u00e9e dans<\/span><b> la cl\u00e9 \u00e9trang\u00e8re<\/b><span style=\"font-weight: 400;\"> (foreign key) de la table de faits pour cr\u00e9er <\/span><b>une relation entre les tables<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Par exemple, une table de faits des ventes (sales fact table) peut avoir une colonne \u00ab ProductID \u00bb qui est une foreign key pointant vers la primary key de la table de dimension produit. Ces relations permettent de croiser les donn\u00e9es de diff\u00e9rentes tables pour obtenir des analyses riches et d\u00e9taill\u00e9es.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8dac8c0 elementor-widget elementor-widget-image\" data-id=\"8dac8c0\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"363\" height=\"380\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image4.webp\" class=\"attachment-full size-full wp-image-255090\" alt=\"\" loading=\"lazy\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image4.webp 363w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image4-287x300.webp 287w\" sizes=\"(max-width: 363px) 100vw, 363px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-ed878ae e-flex e-con-boxed e-con\" data-id=\"ed878ae\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-3078f34 elementor-widget elementor-widget-heading\" data-id=\"3078f34\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Role-Playing Dimensions<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-24b343a elementor-widget elementor-widget-text-editor\" data-id=\"24b343a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Certaines dimensions peuvent jouer diff\u00e9rents r\u00f4les dans le mod\u00e8le de donn\u00e9es. Par exemple, une dimension date peut \u00eatre utilis\u00e9e pour repr\u00e9senter la date de commande, la date de livraison, ou la date de facturation. On parle alors de role-playing dimensions. Cela permet d&rsquo;\u00e9viter la duplication des donn\u00e9es en utilisant une seule dimension pour diff\u00e9rents usages.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-899d448 elementor-widget elementor-widget-image\" data-id=\"899d448\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"786\" height=\"464\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image1.webp\" class=\"attachment-full size-full wp-image-255094\" alt=\"\" loading=\"lazy\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image1.webp 786w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image1-300x177.webp 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2024\/10\/image1-768x453.webp 768w\" sizes=\"(max-width: 786px) 100vw, 786px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-157703d elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"157703d\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formations-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Ma\u00eetriser l'usage d'un data warehouse<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-4448ddc e-flex e-con-boxed e-con\" data-id=\"4448ddc\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-85e0f0e elementor-widget elementor-widget-heading\" data-id=\"85e0f0e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Dimensions \u00e0 \u00e9volution lente (Slowly Changing Dimensions)<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3cfb13c elementor-widget elementor-widget-text-editor\" data-id=\"3cfb13c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Les dimensions peuvent \u00e9voluer au fil du temps, et il est souvent n\u00e9cessaire de suivre ces changements dans le data warehouse. Par exemple, un client peut changer d&rsquo;adresse. <\/span><b>Ces changements doivent \u00eatre g\u00e9r\u00e9s pour \u00eatre capables de comprendre \u00e0 quel moment ces modifications ont eu lieu et comment elles ont affect\u00e9 les faits<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Les<\/span><b> slowly changing dimensions<\/b><span style=\"font-weight: 400;\"> (SCD) permettent de g\u00e9rer ce type de variation. Il existe plusieurs types, notamment :<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Type 1<\/b><span style=\"font-weight: 400;\"> : Le changement remplace simplement l&rsquo;ancienne valeur.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Type 2<\/b><span style=\"font-weight: 400;\"> : Une nouvelle ligne est ajout\u00e9e pour chaque modification, permettant de garder l&rsquo;historique.<\/span><\/li><li><b>Type 3<\/b><span style=\"font-weight: 400;\"> : Une nouvelle colonne est ajout\u00e9e pour garder la pr\u00e9c\u00e9dente valeur.<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-1e108ee e-flex e-con-boxed e-con\" data-id=\"1e108ee\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4c2f502 elementor-widget elementor-widget-heading\" data-id=\"4c2f502\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">L'importance des dimensions dans l'analyse de donn\u00e9es<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4b00dbb elementor-widget elementor-widget-text-editor\" data-id=\"4b00dbb\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Les dimensions permettent de transformer des valeurs num\u00e9riques en informations exploitables. <\/span><b>Elles aident \u00e0 r\u00e9pondre \u00e0 des questions strat\u00e9giques en contexte de business process<\/b><span style=\"font-weight: 400;\">, telles que :\u00a0<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Quel produit se vend le mieux ?\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Qui sont nos meilleurs clients ?<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Quel moment de l&rsquo;ann\u00e9e est le plus rentable ?<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-80f263a elementor-widget elementor-widget-text-editor\" data-id=\"80f263a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">En utilisant des dimensions pertinentes comme le produit, la date, ou le client, les analystes peuvent segmenter les donn\u00e9es de vente ou de production et ainsi obtenir une vue plus pr\u00e9cise des performances de l&rsquo;entreprise. <\/span><b>C&rsquo;est cette association entre facts et dimensions qui rend possible une analyse de donn\u00e9es \u00e9clair\u00e9e.<\/b><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-41dd641 e-flex e-con-boxed e-con\" data-id=\"41dd641\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ba524ab elementor-widget elementor-widget-heading\" data-id=\"ba524ab\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Conclusion<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-14ba911 elementor-widget elementor-widget-text-editor\" data-id=\"14ba911\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Les dimensions sont extr\u00eamement importantes dans un data warehouse et ne doivent pas \u00eatre sous-estim\u00e9es, car elle permettent de <strong>donner du sens aux donn\u00e9es quantitatives<\/strong> contenues dans les tables de faits. En organisant les donn\u00e9es avec des sch\u00e9mas en \u00e9toile ou en flocon de neige, en utilisant les cl\u00e9s primaires et \u00e9trang\u00e8res, et en exploitant des role-playing dimensions, un data warehouse peut fournir une <strong>base solide pour une analyse des donn\u00e9es<\/strong> approfondie.\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-29eaee1 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"29eaee1\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formations-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Tout apprendre sur les data warehouses<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-d92dde4 e-flex e-con-boxed e-con\" data-id=\"d92dde4\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-33fe147 elementor-widget elementor-widget-html\" data-id=\"33fe147\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\r\n{\r\n  \"@context\": \"https:\/\/schema.org\",\r\n  \"@type\": \"FAQPage\",\r\n  \"mainEntity\": [{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Qu'est-ce qu'une table de dimension dans un data warehouse ?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Une table de dimension dans un data warehouse est une table qui stocke les attributs descriptifs li\u00e9s aux donn\u00e9es d'une table de faits. Elle contient des informations qualitatives, comme le nom des produits, les dates, ou les localisations, qui aident \u00e0 donner un contexte aux donn\u00e9es quantitatives pr\u00e9sentes dans les tables de faits.\"\r\n    }\r\n  }, {\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Quelle est la diff\u00e9rence entre une table de faits et une table de dimension ?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"La diff\u00e9rence principale entre une table de faits et une table de dimension est que la table de faits stocke des mesures quantitatives, comme les ventes ou les quantit\u00e9s, tandis que la table de dimension stocke des informations qualitatives qui d\u00e9crivent le contexte de ces mesures, comme les produits, les clients ou les p\u00e9riodes de temps.\"\r\n    }\r\n  }, {\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Quels sont les types de tables de dimension ?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Il existe diff\u00e9rents types de tables de dimension, notamment les dimensions \u00e0 changements lents (SCD - Slowly Changing Dimensions), qui g\u00e8rent les changements d'attributs dans le temps, les dimensions \u00e0 changements rapides, et les dimensions d\u00e9g\u00e9n\u00e9r\u00e9es, o\u00f9 les attributs descriptifs sont stock\u00e9s directement dans la table de faits.\"\r\n    }\r\n  }, {\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Pourquoi les tables de dimension sont-elles importantes dans un data warehouse ?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Les tables de dimension sont essentielles dans un data warehouse car elles fournissent le contexte n\u00e9cessaire pour interpr\u00e9ter les donn\u00e9es stock\u00e9es dans les tables de faits. Elles permettent de structurer les donn\u00e9es de mani\u00e8re \u00e0 faciliter l'analyse, les requ\u00eates, et la g\u00e9n\u00e9ration de rapports d\u00e9cisionnels en offrant une vue d\u00e9taill\u00e9e et descriptive des donn\u00e9es.\"\r\n    }\r\n  }]\r\n}\r\n<\/script>\r\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>En data science et plus pr\u00e9cis\u00e9ment dans les data warehouses, les termes dimension table (table de dimension) et facts table (table de faits) sont des concepts cl\u00e9s dans tout mod\u00e8le de donn\u00e9es, entre autres, \u00e0 des fins d&rsquo;analyse. Rappel : qu&rsquo;est-ce qu&rsquo;un data warehouse ? Un data warehouse est une plateforme centralis\u00e9e de stockage de [&hellip;]<\/p>\n","protected":false},"author":78,"featured_media":255066,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2497],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Tables de dimensions Data Warehouse : les \u00e9l\u00e9ments cl\u00e9s \u00e0 conna\u00eetre<\/title>\n<meta name=\"description\" content=\"D\u00e9couvrez les tables de dimensions pour un Data Warehouse efficace. 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