{"id":1256,"date":"2025-12-26T14:57:02","date_gmt":"2025-12-26T19:57:02","guid":{"rendered":"https:\/\/blog.data-principles.com\/?p=1256"},"modified":"2026-01-06T17:48:33","modified_gmt":"2026-01-06T22:48:33","slug":"data-model-conversion-conceptual-design-to-logical-design-using-an-er-model","status":"publish","type":"post","link":"https:\/\/blog.data-principles.com\/index.php\/2025\/12\/26\/data-model-conversion-conceptual-design-to-logical-design-using-an-er-model\/","title":{"rendered":"Data model conversion: Conceptual design to logical design using an ER model"},"content":{"rendered":"\n<p class=\"has-orange-color has-text-color has-link-color wp-elements-e358becb889ef645eca72e62b736ffc4\"><em>By Pete Stiglich<\/em><\/p>\n\n\n\n<p class=\"has-black-color has-text-color has-link-color wp-elements-25bbe37f25a25eb05ff35798c8f676b5\">Outlines common approaches for transforming a conceptual data model into a logical data model. One approach expands the CDM by identifying additional entities, fully attributizing them with business nomenclature, resolving many\u2011to\u2011many relationships, formalizing keys, handling subtypes, and applying abstraction and normalization. Another approach keeps the LDM closer to an attributized CDM and postpones some resolutions until the physical model, allowing multiple physical manifestations (OLTP vs. dimensional) while maintaining metadata relationships. It emphasizes disciplined steps to avoid semantic drift.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-16018d1d wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link has-orange-background-color has-background wp-element-button\">Read More<\/a><\/div>\n<\/div>\n\n\n\n<p class=\"has-grey-color has-text-color has-link-color wp-elements-215e483ed6eace4cc4c76b0916340335\"><em><strong>Disclaimer<\/strong><\/em> <\/p>\n\n\n\n<p><em>Links to third-party articles and resources are provided for informational purposes only. Data Principles, LLC does not claim ownership of, nor imply endorsement by, the referenced organizations.<\/em><\/p>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:30% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"744\" height=\"746\" src=\"https:\/\/blog.data-principles.com\/wp-content\/uploads\/2025\/12\/Screenshot-2025-06-02-at-3.39.28-PM.png\" alt=\"\" class=\"wp-image-886 size-full\" srcset=\"https:\/\/blog.data-principles.com\/wp-content\/uploads\/2025\/12\/Screenshot-2025-06-02-at-3.39.28-PM.png 744w, https:\/\/blog.data-principles.com\/wp-content\/uploads\/2025\/12\/Screenshot-2025-06-02-at-3.39.28-PM-300x300.png 300w, https:\/\/blog.data-principles.com\/wp-content\/uploads\/2025\/12\/Screenshot-2025-06-02-at-3.39.28-PM-150x150.png 150w\" sizes=\"auto, (max-width: 744px) 100vw, 744px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-orange-color has-text-color has-link-color has-regular-font-size wp-elements-d940b883627d329ff5b661894ecc7ffc\" style=\"text-transform:capitalize\"><strong>Pete Stiglich: Trusted Expert in Data Architecture &amp; Modeling<\/strong><\/p>\n\n\n\n<p class=\"has-text-align-left has-black-color has-text-color has-link-color has-regular-font-size wp-elements-c634ae76efbe08db80e2f28f390bd565\">Pete has over 30 years of data architecture, data management, and analytics experience, most of that time as a consultant in industries such as government, finance, healthcare, insurance, and more.&nbsp;He is an industry thought leader in data architecture and data modeling and has developed and taught many courses on these topics. Pete enjoys helping clients solve complex data problems, leveraging proven approaches such as \u201cModeling the business before modeling the solution\u201d which provides a benefit to clients that many IT professionals miss.<\/p>\n<\/div><\/div>\n\n\n\n<ul class=\"wp-block-social-links is-horizontal is-content-justification-left is-layout-flex wp-container-core-social-links-is-layout-7e5fce0a wp-block-social-links-is-layout-flex\"><li class=\"wp-social-link wp-social-link-linkedin  wp-block-social-link\"><a rel=\"noopener nofollow\" target=\"_blank\" href=\"https:\/\/www.linkedin.com\/in\/petestiglich\/\" class=\"wp-block-social-link-anchor\"><svg width=\"24\" height=\"24\" viewBox=\"0 0 24 24\" version=\"1.1\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M19.7,3H4.3C3.582,3,3,3.582,3,4.3v15.4C3,20.418,3.582,21,4.3,21h15.4c0.718,0,1.3-0.582,1.3-1.3V4.3 C21,3.582,20.418,3,19.7,3z M8.339,18.338H5.667v-8.59h2.672V18.338z M7.004,8.574c-0.857,0-1.549-0.694-1.549-1.548 c0-0.855,0.691-1.548,1.549-1.548c0.854,0,1.547,0.694,1.547,1.548C8.551,7.881,7.858,8.574,7.004,8.574z M18.339,18.338h-2.669 v-4.177c0-0.996-0.017-2.278-1.387-2.278c-1.389,0-1.601,1.086-1.601,2.206v4.249h-2.667v-8.59h2.559v1.174h0.037 c0.356-0.675,1.227-1.387,2.526-1.387c2.703,0,3.203,1.779,3.203,4.092V18.338z\"><\/path><\/svg><span class=\"wp-block-social-link-label screen-reader-text\">LinkedIn<\/span><\/a><\/li>\n\n<li class=\"wp-social-link wp-social-link-mail  wp-block-social-link\"><a rel=\"noopener nofollow\" target=\"_blank\" href=\"mailto:pst&#105;g&#108;&#105;&#099;&#104;&#064;&#100;&#097;&#116;a&#045;&#112;&#114;&#105;nci&#112;&#108;e&#115;&#046;&#099;om\" class=\"wp-block-social-link-anchor\"><svg width=\"24\" height=\"24\" viewBox=\"0 0 24 24\" version=\"1.1\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M19,5H5c-1.1,0-2,.9-2,2v10c0,1.1.9,2,2,2h14c1.1,0,2-.9,2-2V7c0-1.1-.9-2-2-2zm.5,12c0,.3-.2.5-.5.5H5c-.3,0-.5-.2-.5-.5V9.8l7.5,5.6,7.5-5.6V17zm0-9.1L12,13.6,4.5,7.9V7c0-.3.2-.5.5-.5h14c.3,0,.5.2.5.5v.9z\"><\/path><\/svg><span class=\"wp-block-social-link-label screen-reader-text\">Mail<\/span><\/a><\/li><\/ul>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p class=\"has-text-align-center has-blue-color has-text-color has-link-color wp-elements-dc4441a923f3306c286cd692d7ae69ed\" style=\"font-size:26px\"><strong><em>Join Our Data Community<\/em><\/strong><\/p>\n\n\n\n<p class=\"has-text-align-center has-black-color has-text-color has-link-color wp-elements-9bdac29360d2b62aa9e765a3bc163366\">At Data Principles, we believe in making data powerful and accessible. Get monthly insights, practical advice, and company updates delivered straight to your inbox. Subscribe and be part of the journey!<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-16018d1d wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link has-orange-background-color has-background wp-element-button\" href=\"https:\/\/lp.constantcontactpages.com\/sl\/XIYDUv9\/DataDecisionsPathways\">Subscribe  Now<\/a><\/div>\n<\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"946\" height=\"630\" src=\"https:\/\/blog.data-principles.com\/wp-content\/uploads\/2025\/12\/Screenshot-2025-06-02-at-6.34.01-PM.png\" alt=\"\" class=\"wp-image-1087\" style=\"width:450px\" srcset=\"https:\/\/blog.data-principles.com\/wp-content\/uploads\/2025\/12\/Screenshot-2025-06-02-at-6.34.01-PM.png 946w, https:\/\/blog.data-principles.com\/wp-content\/uploads\/2025\/12\/Screenshot-2025-06-02-at-6.34.01-PM-300x200.png 300w, https:\/\/blog.data-principles.com\/wp-content\/uploads\/2025\/12\/Screenshot-2025-06-02-at-6.34.01-PM-768x511.png 768w\" sizes=\"auto, (max-width: 946px) 100vw, 946px\" \/><\/figure><\/div>","protected":false},"excerpt":{"rendered":"<p>By Pete Stiglich Outlines common approaches for transforming a conceptual data model into a logical data model. One approach expands the CDM by identifying additional&hellip;<\/p>\n","protected":false},"author":5,"featured_media":1257,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[258],"tags":[172,209,83,85,119,87,127,210,201,121],"class_list":["post-1256","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-modeling","tag-analytics-2","tag-conceptual-design","tag-data-architecture","tag-data-modeling","tag-data-strategy","tag-enterprise-data","tag-er-modeling","tag-logical-design","tag-quality-by-design","tag-semantic-modeling"],"_links":{"self":[{"href":"https:\/\/blog.data-principles.com\/index.php\/wp-json\/wp\/v2\/posts\/1256","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.data-principles.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.data-principles.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.data-principles.com\/index.php\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.data-principles.com\/index.php\/wp-json\/wp\/v2\/comments?post=1256"}],"version-history":[{"count":1,"href":"https:\/\/blog.data-principles.com\/index.php\/wp-json\/wp\/v2\/posts\/1256\/revisions"}],"predecessor-version":[{"id":1258,"href":"https:\/\/blog.data-principles.com\/index.php\/wp-json\/wp\/v2\/posts\/1256\/revisions\/1258"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.data-principles.com\/index.php\/wp-json\/wp\/v2\/media\/1257"}],"wp:attachment":[{"href":"https:\/\/blog.data-principles.com\/index.php\/wp-json\/wp\/v2\/media?parent=1256"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.data-principles.com\/index.php\/wp-json\/wp\/v2\/categories?post=1256"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.data-principles.com\/index.php\/wp-json\/wp\/v2\/tags?post=1256"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}