{"id":191307,"date":"2024-12-03T06:40:00","date_gmt":"2024-12-03T05:40:00","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=191307"},"modified":"2024-12-04T20:21:34","modified_gmt":"2024-12-04T19:21:34","slug":"all-about-dimension-tables","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/all-about-dimension-tables","title":{"rendered":"What are Dimension tables in a Data Warehouse?"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"191307\" class=\"elementor elementor-191307\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1a55f33 e-flex e-con-boxed e-con\" data-id=\"1a55f33\" 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-0bed439 elementor-widget elementor-widget-text-editor\" data-id=\"0bed439\" 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><b>In data science, and more specifically in data warehouses, the terms dimension table and fact table are essential concepts in any data model, among others, for analysis purposes.<\/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-08779c3 e-flex e-con-boxed e-con\" data-id=\"08779c3\" 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-3ef859b e-con-full e-flex e-con\" data-id=\"3ef859b\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-bc9f6b1 elementor-widget elementor-widget-image\" data-id=\"bc9f6b1\" 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\/en\/files\/2024\/11\/image3-1.webp\" class=\"attachment-large size-large wp-image-191313\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/11\/image3-1.webp 512w, https:\/\/datascientest.com\/en\/files\/2024\/11\/image3-1-300x300.webp 300w, https:\/\/datascientest.com\/en\/files\/2024\/11\/image3-1-150x150.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-13eef52 e-con-full e-flex e-con\" data-id=\"13eef52\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-fd4106a elementor-widget elementor-widget-heading\" data-id=\"fd4106a\" 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\">Reminder: What is a Data Warehouse?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d316167 elementor-widget elementor-widget-text-editor\" data-id=\"d316167\" 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><a href=\"https:\/\/datascientest.com\/en\/data-warehouse-2\"><span style=\"font-weight: 400;\">A data warehouse is a centralized data storage platform<\/span><\/a><span style=\"font-weight: 400;\"> designed to facilitate analysis and decision-making. It consolidates data from various sources and organizes it in a manner that supports fast and efficient analysis. Unlike operational databases, a data warehouse is optimized for <\/span><b>historical data analysis<\/b><span style=\"font-weight: 400;\">, thus providing a comprehensive view of past and current performance.<\/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-0c3a1e6 e-flex e-con-boxed e-con\" data-id=\"0c3a1e6\" 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-86fe729 elementor-widget elementor-widget-heading\" data-id=\"86fe729\" 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\">What is a Dimension Table?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d7e0603 elementor-widget elementor-widget-text-editor\" data-id=\"d7e0603\" 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>A dimension is a table that stores qualitative attributes<\/b><span style=\"font-weight: 400;\"> of a key element within the business process. These attributes serve to describe <\/span><b>numerical facts<\/b><span style=\"font-weight: 400;\">, which are recorded in the fact tables.<\/span><\/p><p><span style=\"font-weight: 400;\">Dimensions thus offer context for quantitative measures. They provide details about events, such as who made a sale, when, where, or to which product the sale was made.<\/span><\/p><p><span style=\"font-weight: 400;\">These attributes can include items like the product, date, customer, or even location. Dimension tables are structured to make data analysis intuitive, thus making it easier to comprehend <\/span><b>fact tables, which contain quantitative measures.<\/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-2a2d9d9 e-flex e-con-boxed e-con\" data-id=\"2a2d9d9\" 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-3b83af1 elementor-widget elementor-widget-heading\" data-id=\"3b83af1\" 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\">Types of Schemas Used<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-127d1c9 elementor-widget elementor-widget-text-editor\" data-id=\"127d1c9\" 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;\">There are several models for organizing fact and dimension tables, including star schemas and snowflake schemas.<\/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-680e0af e-flex e-con-boxed e-con\" data-id=\"680e0af\" 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-0842cd9 e-con-full e-flex e-con\" data-id=\"0842cd9\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-958ccfe elementor-widget elementor-widget-image\" data-id=\"958ccfe\" 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\/en\/files\/2024\/11\/image5-1.webp\" class=\"attachment-full size-full wp-image-191320\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/11\/image5-1.webp 848w, https:\/\/datascientest.com\/en\/files\/2024\/11\/image5-1-300x205.webp 300w, https:\/\/datascientest.com\/en\/files\/2024\/11\/image5-1-768x524.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-0cc85f2 e-con-full e-flex e-con\" data-id=\"0cc85f2\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d97ba68 elementor-widget elementor-widget-heading\" data-id=\"d97ba68\" 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-1f1add9 elementor-widget elementor-widget-text-editor\" data-id=\"1f1add9\" 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;\">This schema type is the simplest and most commonly employed in data warehousing. Here, fact tables are positioned at the center and linked to the surrounding dimension tables, forming a star-shaped structure. This configuration facilitates data analysis due to the clear and uncomplicated table relationships. It is generally the preferred approach where feasible.<\/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-e211514 e-flex e-con-boxed e-con\" data-id=\"e211514\" 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-99f3146 e-con-full e-flex e-con\" data-id=\"99f3146\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-27b342b elementor-widget elementor-widget-image\" data-id=\"27b342b\" 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\/en\/files\/2024\/11\/image2-1.webp\" class=\"attachment-full size-full wp-image-191321\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/11\/image2-1.webp 1200w, https:\/\/datascientest.com\/en\/files\/2024\/11\/image2-1-300x181.webp 300w, https:\/\/datascientest.com\/en\/files\/2024\/11\/image2-1-1024x619.webp 1024w, https:\/\/datascientest.com\/en\/files\/2024\/11\/image2-1-768x464.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-c40c64f e-con-full e-flex e-con\" data-id=\"c40c64f\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-882324d elementor-widget elementor-widget-heading\" data-id=\"882324d\" 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-f1e2d97 elementor-widget elementor-widget-text-editor\" data-id=\"f1e2d97\" 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;\">The snowflake schema is an extension of the star schema, where dimension tables are normalized into multiple tiers. This signifies that the attributes of a dimension are further linked to other tables, forming a more intricate structure that resembles a snowflake. This approach reduces data redundancy but increases the complexity of the queries.<\/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-18b17d9 e-flex e-con-boxed e-con\" data-id=\"18b17d9\" 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-b266ab9 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"b266ab9\" 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-md\" href=\"https:\/\/datascientest.com\/en\/data-courses\">\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\">Learn all about 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-e723c69 e-flex e-con-boxed e-con\" data-id=\"e723c69\" 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-bf75bd3 elementor-widget elementor-widget-heading\" data-id=\"bf75bd3\" 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 and Foreign Keys<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-da486f6 elementor-widget elementor-widget-text-editor\" data-id=\"da486f6\" 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;\">In a dimensional model, dimension tables have a <\/span><b>primary key<\/b><span style=\"font-weight: 400;\"> that <\/span><b>uniquely identifies each row<\/b><span style=\"font-weight: 400;\">. This primary key is subsequently used in the <\/span><b>foreign key<\/b><span style=\"font-weight: 400;\"> of the fact table to establish <\/span><b>a relationship between the tables<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">For instance, a sales fact table might include a &#8220;ProductID&#8221; column that serves as a foreign key pointing to the primary key of the product dimension table. These relationships allow data from different tables to be combined for rich and detailed analyses.<\/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-572e0dd elementor-widget elementor-widget-image\" data-id=\"572e0dd\" 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\/en\/files\/2024\/11\/image4-1.webp\" class=\"attachment-full size-full wp-image-191328\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/11\/image4-1.webp 363w, https:\/\/datascientest.com\/en\/files\/2024\/11\/image4-1-287x300.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-7887fde e-flex e-con-boxed e-con\" data-id=\"7887fde\" 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-2be10a8 elementor-widget elementor-widget-heading\" data-id=\"2be10a8\" 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-99cbf2b elementor-widget elementor-widget-text-editor\" data-id=\"99cbf2b\" 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;\">Some dimensions can assume different roles within the data model. For example, a date dimension can represent order date, delivery date, or billing date. These are referred to as role-playing dimensions. This approach prevents data duplication by utilizing a single dimension for various purposes.<\/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-0e5b993 elementor-widget elementor-widget-image\" data-id=\"0e5b993\" 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\/en\/files\/2024\/11\/image1-1.webp\" class=\"attachment-full size-full wp-image-191329\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/11\/image1-1.webp 786w, https:\/\/datascientest.com\/en\/files\/2024\/11\/image1-1-300x177.webp 300w, https:\/\/datascientest.com\/en\/files\/2024\/11\/image1-1-768x453.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-6762039 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"6762039\" 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-md\" href=\"https:\/\/datascientest.com\/en\/data-scientist-course\">\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\">Follow a course in Data Science<\/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-d2b6a13 e-flex e-con-boxed e-con\" data-id=\"d2b6a13\" 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-cd9bc2d elementor-widget elementor-widget-heading\" data-id=\"cd9bc2d\" 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\">Slowly Changing Dimensions (SCD)<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a8e5431 elementor-widget elementor-widget-text-editor\" data-id=\"a8e5431\" 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;\">Dimensions can evolve over time, necessitating the tracking of these changes within the data warehouse. For example, a customer may update their address. <\/span><b>These changes must be managed to understand when these modifications occurred and how they impacted the facts<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><b>Slowly changing dimensions<\/b><span style=\"font-weight: 400;\"> (SCD) enable the management of these types of variations. There are several types, including:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Type 1<\/b><span style=\"font-weight: 400;\">: The change simply overwrites the old value.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Type 2<\/b><span style=\"font-weight: 400;\">: A new row is added for each change, preserving history.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Type 3<\/b><span style=\"font-weight: 400;\">: A new column is added to keep the previous value.<\/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-1799a89 e-flex e-con-boxed e-con\" data-id=\"1799a89\" 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-c1a0869 elementor-widget elementor-widget-heading\" data-id=\"c1a0869\" 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\">The Importance of Dimensions in Data Analysis<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9f75260 elementor-widget elementor-widget-text-editor\" data-id=\"9f75260\" 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;\">Dimensions transform numerical values into actionable information. <\/span><b>They help answer strategic questions in the context of a business process<\/b><span style=\"font-weight: 400;\">, such as:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Which product is the best-selling?<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Who are our top customers?<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">What time of year is the most profitable?<\/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-babdf33 elementor-widget elementor-widget-text-editor\" data-id=\"babdf33\" 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;\">By using relevant dimensions like product, date, or customer, analysts can segment sales or production data to gain a more accurate perspective of the company&#8217;s performance. <\/span><b>This association between facts and dimensions enables informed data analysis.<\/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-c6dec9a e-flex e-con-boxed e-con\" data-id=\"c6dec9a\" 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-eb7a1c7 elementor-widget elementor-widget-heading\" data-id=\"eb7a1c7\" 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-eee3f2f elementor-widget elementor-widget-text-editor\" data-id=\"eee3f2f\" 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;\">Dimensions are crucial in a data warehouse and should not be underestimated, as they help <\/span><b>provide meaning to the quantitative data<\/b><span style=\"font-weight: 400;\"> contained in the fact tables. By organizing data using star or snowflake schemas, employing primary and foreign keys, and leveraging role-playing dimensions, a data warehouse can offer a <\/span><b>solid foundation for comprehensive data analysis.<\/b><\/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-f57b2a5 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"f57b2a5\" 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-md\" href=\"https:\/\/datascientest.com\/en\/data-analyst-course\">\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\">Become a Data Analyst<\/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-253a65a e-flex e-con-boxed e-con\" data-id=\"253a65a\" 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-8629627 elementor-widget elementor-widget-html\" data-id=\"8629627\" 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    {\r\n      \"@type\": \"Question\",\r\n      \"name\": \"What is a dimension table in a data warehouse?\",\r\n      \"acceptedAnswer\": {\r\n        \"@type\": \"Answer\",\r\n        \"text\": \"A dimension table in a data warehouse is a table that stores descriptive attributes related to the data in a fact table. 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It consolidates data from various sources [&hellip;]<\/p>\n","protected":false},"author":45,"featured_media":191309,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2425],"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>What are Dimension tables in a Data Warehouse?<\/title>\n<meta name=\"description\" content=\"Discover dimension tables for an efficient Data Warehouse. 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