{ "source_file": "0930", "source_platform": "Ghost", "author": "Deep Learning Nerds", "title_listed": "Configuring dbt Model Access using Grants: A Practical Example", "keywords": "", "domain": "大模型算法", "content_type": "技术教程", "is_paid_flag": "否", "url": "https://www.deeplearningnerds.com/configuring-dbt-model-access-using-grants-practical-example/", "publish_date": "2026-06", "corpus_stage": "", "notes": "", "id": "24d6368e6a19", "collected_at": "2026-10-02T12:22:38", "title": "Configuring dbt Model Access using Grants: A Practical Example", "body_markdown": "📘 Introduction\nAccess control is an important part of every analytics project. Not every role should be able to query every model in your warehouse.\nWe use the same\ndlnerds_university\nMedallion Architecture example project from previous dbt posts, so the project structure stays familiar. In this tutorial, you will learn how to configure dbt model access with\ngrants\n.\nThe example is simple: the role\ndata_engineer\nshould be able to query all dbt models, the role\ndata_analyst\nshould only be able to query Gold models in\n03_gold\n, and the role\ndata_scientist\nshould only be able to query\ndim_student\n.\n💡 What are we implementing?\nWe will configure this access pattern:\ndata_engineer -> Access to Silver and Gold models\ndata_analyst -> Access only to Gold models\ndata_scientist -> Access only to dim_student\nIn our Medallion Architecture project, Bronze contains raw source table definitions in\nmodels/01_bronze/sources.yml\nand no dbt SQL models. Silver contains cleaned dbt models in\n02_silver\n. Gold contains business-ready dbt models in\n03_gold\n.\n💡\ndbt\ngrants\napply to dbt-created models, seeds, and snapshots. Raw source tables and schema-level permissions may still need separate warehouse permissions, depending on your data platform.\n✅ Prerequisites\n☑️ A working dbt project\n☑️ Raw source tables already loaded into the warehouse or local database\n☑️ Raw source tables already defined in\nmodels/01_bronze/sources.yml\n☑️ Existing Silver model\nstudent_cleaned\nwith its own YAML file\n☑️ Warehouse roles or grantees named\ndata_engineer\n,\ndata_analyst\n, and\ndata_scientist\n☑️ Permission to grant access on the target database objects\n🧱1️⃣ Understand the project structure\nFor this tutorial, we use this relevant excerpt of the\ndlnerds_university\nproject:\ndlnerds_university/\n├── dbt_project.yml\n└── models/\n ├── 01_bronze/\n │ └── sources.yml\n ├── 02_silver/\n │ ├── student_cleaned.sql\n │ └── student_cleaned.yml\n └── 03_gold/\n ├── dim_student.sql\n └── dim_student.yml\nThe important part is the model folder structure. We want a broad grant for all models and a more specific grant for the Gold folder.\n🔐2️⃣ Understand the access rule\nBefore writing dbt config, define the rule in plain English:\ndata_engineer\ngets\nselect\naccess on every dbt model in the project.\ndata_analyst\ngets\nselect\naccess only on models in\nmodels/03_gold\n.\ndata_scientist\ngets\nselect\naccess only on\ndim_student\n.\nSilver models stay hidden from analysts and data scientists, unless another warehouse permission gives them access.\nThis is a common pattern: engineers can inspect intermediate models, analysts consume business-ready Gold models, and a specialized role can access one specific model.\n🎓 Want to go deeper with dbt?\nIf you want to become confident with dbt project structure, access control, model configuration, and Medallion Architecture workflows, the Academy gives you more hands-on examples with real project patterns.\nIf you’d like to dive deeper into\ndbt (data build tool)\n, our book\nBuilding Modern Data Pipelines with dbt: From Raw Data to Gold Standard with the Medallion Architecture\nprovides a hands-on guide to designing modern data pipelines. It covers dbt’s core concepts and best practices, including building Bronze, Silver, and Gold layers with the\nMedallion Architecture\n. It also serves as a hands-on study guide for the\ndbt Analytics Engineering Certification\n.\nView on Amazon\nYou can view this post with the tier:\n Academy Membership\nJoin academy now to read the post and get access to the full library of premium posts for academy members only.\nJoin Academy\nAlready have an account?\nSign In", "metadata": { "title": "Configuring dbt Model Access using Grants: A Practical Example", "description": "Learn how to configure dbt grants so data engineers can query all models, data analysts can query Gold models, and data scientists can query one specific model.", "keywords": null, "author": null, "og:site_name": "Deep Learning Nerds | The ultimate Learning Platform for AI and Data Science", "og:type": "article", "og:title": "Configuring dbt Model Access using Grants: A Practical Example", "og:description": "Learn how to configure dbt grants so data engineers can query all models, data analysts can query Gold models, and data scientists can query one specific model.", "og:url": "https://www.deeplearningnerds.com/configuring-dbt-model-access-using-grants-practical-example/", "og:image": "https://storage.ghost.io/c/5b/26/5b26e983-a59f-4f4b-a5f2-bd8c5a0a38e2/content/images/size/w1200/2026/06/dbt---Configuring-dbt-Model-Access-using-Grants-A-Practical-Example.png", "og:image:width": "1200", "og:image:height": "839", "twitter:card": "summary_large_image", "twitter:title": "Configuring dbt Model Access using Grants: A Practical Example", "twitter:description": "Learn how to configure dbt grants so data engineers can query all models, data analysts can query Gold models, and data scientists can query one specific model.", "twitter:url": "https://www.deeplearningnerds.com/configuring-dbt-model-access-using-grants-practical-example/", "twitter:image": "https://storage.ghost.io/c/5b/26/5b26e983-a59f-4f4b-a5f2-bd8c5a0a38e2/content/images/size/w1200/2026/06/dbt---Configuring-dbt-Model-Access-using-Grants-A-Practical-Example.png", "twitter:label1": "Written by", "twitter:data1": "Data Engineer", "twitter:label2": "Filed under", "twitter:data2": "dbt, Data Engineering, dbt Analytics Engineering Certification", "twitter:site": "@DLNerds", "article:published_time": "2026-06-05T12:48:08.000Z", "article:modified_time": "2026-06-05T12:48:08.000Z", "article:tag": "dbt Analytics Engineering Certification", "article:publisher": "https://www.facebook.com/deeplearningnerds/", "article:author": "https://www.facebook.com/deeplearningnerds/" }, "paywall": { "listed_paid": false, "detected": false, "marker": "", "public_only": false, "policy": "付费/会员内容只保留页面公开可见部分，不绕过付费墙" }, "crawl": { "success": true, "status_code": 200, "error": "" }, "code_blocks": [ { "file": "attachments/24d6368e6a19/code/body-000.txt", "chars": 140, "language": "text" }, { "file": "attachments/24d6368e6a19/code/body-001.txt", "chars": 250, "language": "text" } ], "images": [ { "status": "ok", "url": "https://storage.ghost.io/c/5b/26/5b26e983-a59f-4f4b-a5f2-bd8c5a0a38e2/content/images/2026/03/Mockup-Transparent-PNG-1.png", "bytes": 1130793, "reused": true, "local_path": "attachments/24d6368e6a19/images/005.png", "src": "https://storage.ghost.io/c/5b/26/5b26e983-a59f-4f4b-a5f2-bd8c5a0a38e2/content/images/2026/03/Mockup-Transparent-PNG-1.png", "alt": "CTA Image", "downloaded": true } ], "audio": [], "videos": [], "links": [ { "href": "https://amzn.eu/d/04HPLJMo?ref=deeplearningnerds.com", "label": "", "type": "a" }, { "href": "https://www.deeplearningnerds.com/membership/", "label": "Join Academy", "type": "a" }, { "href": "https://www.deeplearningnerds.com/signin/", "label": "Sign In", "type": "a" } ], "repair_version": 2, "repaired_at": "2026-10-14T10:47:42Z", "source_url": "https://www.deeplearningnerds.com/configuring-dbt-model-access-using-grants-practical-example/", "papers": [], "actual_video_files": [], "body_chars": 3645, "expected_body_images": 1, "discovery_status": "ok", "delivery_status": "ok", "missing_reason": "", "raw_html": "attachments/24d6368e6a19/pages/source.html", "local_html": "attachments/24d6368e6a19/pages/article.html", "body_base_path": "attachments/24d6368e6a19/pages/", "body_markdown_path": "attachments/24d6368e6a19/pages/article.md" }