{"id":23585158,"url":"https://github.com/chaseofthejungle/data-repositories-overview","last_synced_at":"2026-01-30T16:02:53.166Z","repository":{"id":267705128,"uuid":"902092326","full_name":"chaseofthejungle/data-repositories-overview","owner":"chaseofthejungle","description":"A quick guide to several different kinds of data repositories and their use cases.","archived":false,"fork":false,"pushed_at":"2025-05-18T16:07:45.000Z","size":14,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-04T05:33:53.038Z","etag":null,"topics":["data-architecture","data-repository","data-warehousing"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/chaseofthejungle.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2024-12-11T22:24:14.000Z","updated_at":"2025-05-18T16:07:48.000Z","dependencies_parsed_at":"2024-12-12T00:18:45.659Z","dependency_job_id":"929f0a42-f4e7-41da-91c3-8d04f564e1f0","html_url":"https://github.com/chaseofthejungle/data-repositories-overview","commit_stats":null,"previous_names":["chaseofthejungle/data-repositories-overview"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/chaseofthejungle/data-repositories-overview","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chaseofthejungle%2Fdata-repositories-overview","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chaseofthejungle%2Fdata-repositories-overview/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chaseofthejungle%2Fdata-repositories-overview/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chaseofthejungle%2Fdata-repositories-overview/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/chaseofthejungle","download_url":"https://codeload.github.com/chaseofthejungle/data-repositories-overview/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chaseofthejungle%2Fdata-repositories-overview/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28914938,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-30T12:13:43.263Z","status":"ssl_error","status_checked_at":"2026-01-30T12:13:22.389Z","response_time":66,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-architecture","data-repository","data-warehousing"],"created_at":"2024-12-27T03:14:10.667Z","updated_at":"2026-01-30T16:02:53.153Z","avatar_url":"https://github.com/chaseofthejungle.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data Repositories Overview\n  \n#### Table of Contents:\n  \n1. [Six Data Repository Types/Architectures](#data-repository)\n2. [Data-Characteristic Terms](#data-terms)\n3. [Supplemental Resources](#supplemental)\n  \n\u003chr /\u003e\n  \n## 1. \u003ca name=\"data-repository\"\u003eSix Data Repository Types/Architectures\u003c/a\u003e\n  \n* **Data Fabric**\n  + Allows for distributed data to be quickly/easily accessed, managed, and integrated.\n    - This unites data from various sources and provides orchestration, governance, and virtualization.\n  + Data silos (data separated from other parts of an organization's system) can be easily accessed and have their data analyzed.\n    - This supports concentrated and informed decision-making.\n* **Data Lake**\n  + Stores structured, semi-structured, *and* unstructured ('raw') data in a large and centralized manner.\n  + Pulls data from multiple (or even many) sources, for both analysis and processing.\n  + Data models and schemas are not applied (data are in their native formats).\n    - This allows for quick and adaptive data analysis and reading.\n      + Machine learning and complex analytics/reporting can pull from various kinds of data, due to data lake integration.\n* **Data Mart**\n  + A specialized data warehouse subset (smaller in size and scope and concentrated on a single purpose/subject).\n  + Data marts can satisfy both departmental *and* specific business needs by focusing on directly relevant data.\n    - Schemas and data models are tailored to specific data analysis/reporting/decision-making purposes.\n* **Data Mesh**\n  + Scalable, accessible, and decentralized through a domain-driven data ownership model.\n    - Data are distributed to data owners as self-service products, with potential for data sharing/collaboration and feedback.\n      + Owners/managers across an organization can conveniently claim their data.\n    - Popular in enterprise environments, because data governance and scalability can get complicated (and bottleneck productivity).\n* **Data Pipeline**\n  + Transfers data from source to target/destination systems, for convenient data storage and/or analysis.\n* **Data Warehouse**\n  + Stores structured data in an organized system, with the potential for data tracking/logging.\n    - Popular for business intelligence (BI), decision support, and reporting tools (especially due to consistent data formatting).\n    - Data structure is provided through the use of schemas and models, which are predefined by developers/engineers.\n    - Data transformation from source systems to a consistent data warehouse format is referred to as an 'extracted, transformed, and loaded', or 'ETL', process.\n\n\u003chr /\u003e\n  \n## 2. \u003ca name=\"data-terms\"\u003eData-Characteristic Terms\u003c/a\u003e\n\n* **Data Observability**\n  + Observing the performance of, and tracking/monitoring, data at any point in its lifecycle.\n* **Data Quality**\n  + How accurate and consistent data are.\n    - Can the data be used to perform reliable analysis and make informed decisions?\n  \n\u003chr /\u003e\n\n## 3. \u003ca name=\"supplemental\"\u003eSupplemental Resources\u003c/a\u003e\n  \n* *[Data Analysis Tools Overview Guide](https://github.com/chaseofthejungle/data-analysis-tools-overview-guide)*\n* *[Overview of Database Types](https://github.com/chaseofthejungle/types-of-databases)*\n* *[Intro to Structured Query Language (SQL)](https://github.com/chaseofthejungle/intro-to-sql/)*\n  \n\u003chr /\u003e\n  \nTODO: Add examples of different data repo types and how they operate.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchaseofthejungle%2Fdata-repositories-overview","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchaseofthejungle%2Fdata-repositories-overview","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchaseofthejungle%2Fdata-repositories-overview/lists"}