{"id":16030,"date":"2022-08-10T11:45:47","date_gmt":"2022-08-10T15:45:47","guid":{"rendered":"https:\/\/enterprise-knowledge.com\/?p=16030"},"modified":"2024-01-09T14:20:14","modified_gmt":"2024-01-09T19:20:14","slug":"why-your-data-fabric-needs-an-enterprise-ontology","status":"publish","type":"post","link":"https:\/\/enterprise-knowledge.com\/why-your-data-fabric-needs-an-enterprise-ontology\/","title":{"rendered":"Why Your Data Fabric Needs an Enterprise Ontology"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">In today\u2019s rapidly growing and evolving data environment, it is increasingly difficult for organizations to get maximal value from the full breadth of their data. As more data is produced faster by more sources, it is difficult for analysts, data scientists, and other consumers to be aware of and effectively use data being produced across organizational divisions and domain areas. Impaired discovery and use of data can lead to the direct costs of duplicated effort and wasted time, as well as the opportunity costs of unrealized data-driven insights.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The <\/span><strong><a href=\"https:\/\/enterprise-knowledge.com\/data-management-trends-in-2022-data-fabric-v-data-mesh-v-dataops-what-is-right-for-your-organization\/\" target=\"_blank\" rel=\"noopener\">concept of data fabric<\/a><\/strong><span style=\"font-weight: 400;\"> is increasingly recognized as a key solution to the growing challenges of the modern data ecosystem, utilizing an enterprise-wide data architecture to facilitate discovery and use across the organization. Supporting your data fabric with an ontology\u2013a graph-based semantic model that describes your organization\u2019s data using standardized classes and concepts\u2013amplifies the benefits of the data fabric, allowing your organization to:\u00a0<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Discover and operationalize connections among distributed data;\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Facilitate the integration of data across sources and use cases; and<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Implement more robust data management and governance.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">At EK we have had <\/span><strong><a href=\"https:\/\/enterprise-knowledge.com\/knowledge-base\/?fwp_article_type=case-study\" target=\"_blank\" rel=\"noopener\">repeated success drawing on our experience developing ontologies and implementing semantic architectures to provide data fabric solutions<\/a><\/strong><span style=\"font-weight: 400;\"> to our clients. These successes have demonstrated tangible ways in which an enterprise ontology empowers a data fabric and magnifies its benefits, and have allowed us to identify concrete steps an organization can take toward designing, piloting, and scaling its own ontology-powered data fabric architecture.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">What is a Data Fabric?<\/span><\/h2>\n<p><a href=\"https:\/\/enterprise-knowledge.com\/data-management-trends-in-2022-data-fabric-v-data-mesh-v-dataops-what-is-right-for-your-organization\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\"><strong>Data fabric<\/strong><\/span><\/a><span style=\"font-weight: 400;\"> is a logical data architecture that connects data assets across an organization and enriches them with standardized semantic metadata. The core of the data fabric is an abstraction layer that uses data virtualization to bring together information about data sources in disparate formats, systems, and locations while applying standardized processes for data governance, privacy, and security. By connecting data as if it were housed together, the data fabric makes it findable and usable without the overhead cost of actually moving the data into a single repository, which could require substantial intermediary processing and the maintenance of redundant infrastructure<\/span><i><span style=\"font-weight: 400;\">.<\/span><\/i><\/p>\n<p><span style=\"font-weight: 400;\">A data fabric can also include components that use knowledge inference, machine learning, or other AI systems to automate integration, orchestration, and metadata management across the systems touched by the data fabric.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">What is an ontology?<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">An <\/span><strong><a href=\"https:\/\/enterprise-knowledge.com\/what-is-an-ontology\/\" target=\"_blank\" rel=\"noopener\">ontology<\/a><\/strong><span style=\"font-weight: 400;\"> is a semantic model that defines the concepts in a particular domain area, their attributes, and the relationships between them, encoding them in a graph format that is both machine- and human-readable. Most of the time, an ontology is a generalized model, describing the kinds of entities and relationships that exist in a domain rather than describing specific entities in the domain. For example, an e-commerce business might model the domain area surrounding its fulfillment operations as an ontology with entities such as <\/span><i><span style=\"font-weight: 400;\">Customer<\/span><\/i><span style=\"font-weight: 400;\">, <\/span><i><span style=\"font-weight: 400;\">Item<\/span><\/i><span style=\"font-weight: 400;\">, and <\/span><i><span style=\"font-weight: 400;\">Order<\/span><\/i><span style=\"font-weight: 400;\">; attributes such as <\/span><i><span style=\"font-weight: 400;\">Name<\/span><\/i><span style=\"font-weight: 400;\">, <\/span><i><span style=\"font-weight: 400;\">Phone Number<\/span><\/i><span style=\"font-weight: 400;\">, <\/span><i><span style=\"font-weight: 400;\">Quantity<\/span><\/i><span style=\"font-weight: 400;\">, and <\/span><i><span style=\"font-weight: 400;\">Product ID<\/span><\/i><span style=\"font-weight: 400;\">; and relationships such as <\/span><i><span style=\"font-weight: 400;\">Places<\/span><\/i><span style=\"font-weight: 400;\"> and <\/span><i><span style=\"font-weight: 400;\">Contains<\/span><\/i><span style=\"font-weight: 400;\">:<\/span><\/p>\n<p><a href=\"https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/1-Ontology-Model.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-16033 size-large\" src=\"https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/1-Ontology-Model-771x364.png\" alt=\"An ontology describing the essential components of a business's fulfillment operation. A customer entity can have phone number and name attributes. An item entity can have quantity and product ID attributes. An order entity can contain an item entity using the 'contains' relationship, and a customer entity can place an order using the 'places' relationship.\" width=\"640\" height=\"302\" srcset=\"https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/1-Ontology-Model-771x364.png 771w, https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/1-Ontology-Model-336x159.png 336w, https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/1-Ontology-Model-768x363.png 768w, https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/1-Ontology-Model.png 1072w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><\/p>\n<p style=\"text-align: center;\"><em>This simple ontology describes the entities involved in a business\u2019s fulfillment operations processes (customers, orders, and items), their attributes (phone numbers, names, quantities, and product IDs), and the relationships between them (a customer places an order, an order contains an item).<\/em><\/p>\n<p>&nbsp;<\/p>\n<p style=\"text-align: left;\"><span style=\"font-weight: 400;\">In addition to providing a model that bakes in the meaning of data elements, ontologies can also be used to support many advanced AI technologies, including <\/span><strong><a href=\"https:\/\/enterprise-knowledge.com\/why-invest-in-a-knowledge-graph-your-digital-transformation-and-enterprise-ai-initiatives-depend-on-it\/\" target=\"_blank\" rel=\"noopener\">knowledge graphs<\/a><\/strong><span style=\"font-weight: 400;\"> and <\/span><strong><a href=\"https:\/\/enterprise-knowledge.com\/a-course-recommendation-system-based-on-a-knowledge-graph\/\" target=\"_blank\" rel=\"noopener\">recommendation engines<\/a><\/strong><span style=\"font-weight: 400;\">.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">How Does an Enterprise Ontology Support a Data Fabric?<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Developing an enterprise ontology to power semantic metadata is central to implementing an effective data fabric. The ontology provides the data fabric with an interoperable schema to standardize, enrich, and reconcile source data, giving users and applications a unified and reliable view of data across disparate data sources.<\/span><\/p>\n<p><a href=\"https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/2-Data-Fabric-Architecture.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-16035 size-large\" src=\"https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/2-Data-Fabric-Architecture-e1660144863796-771x537.png\" alt=\"An architecture diagram showing a data fabric layer mediating between data sources and data consumers. The data fabric is comprised of an enterprise ontology and other systems such as a data catalog, data orchestration, and a knowledge graph. Information about data sources (such as a data lake, data warehouse, content management system, or external data sources) flows into the data fabric, which connects that information with data consumers (such as research teams, analysts, and applications).\" width=\"640\" height=\"446\" srcset=\"https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/2-Data-Fabric-Architecture-e1660144863796-771x537.png 771w, https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/2-Data-Fabric-Architecture-e1660144863796-336x234.png 336w, https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/2-Data-Fabric-Architecture-e1660144863796-768x535.png 768w, https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/2-Data-Fabric-Architecture-e1660144863796.png 960w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><\/p>\n<p style=\"text-align: center;\"><em>The enterprise ontology serves machine-readable meaning and business logic to the other systems of the data fabric, allowing the fabric to integrate data sources and make them available to data consumers.<\/em><\/p>\n<h3 style=\"text-align: left;\"><span style=\"font-weight: 400;\">Discover and Operationalize Connections<\/span><\/h3>\n<p style=\"text-align: left;\"><span style=\"font-weight: 400;\">By providing an interoperable, system-agnostic semantic foundation, an enterprise ontology enables you to discover and operationalize connections among data assets. Unlike traditional relational and NoSQL data schemas, an ontology explicitly embeds the meaning of data concepts and the relationships that connect them within the data model itself. This means that data producers and consumers can reliably identify data assets across the organization that are using the same data elements as well as identify trustable connections to other data assets, even if all of the data involved uses divergent terminology.<\/span><\/p>\n<p style=\"text-align: left;\"><span style=\"font-weight: 400;\">For example, a data fabric using the sample customer ontology above would be able to automatically connect two datasets with differently named columns mapping to Phone Number, allowing analysts to confidently join tables on those columns and helping to surface these related datasets to data scientists. These machine-readable connections can also power recommendation engines and other advanced AI integrations that help you make the most of your organization\u2019s data.<\/span><\/p>\n<h3 style=\"text-align: left;\"><span style=\"font-weight: 400;\">Facilitate Data Integration<\/span><\/h3>\n<p style=\"text-align: left;\"><span style=\"font-weight: 400;\">An ontology\u2019s data model is also highly flexible and extensible, which allows it to act as a system-agnostic conceptual model for the organization\u2019s data ecosystem, facilitating the integration of data from diverse sources and use cases. As new data is created, ingested, and unearthed, new classes and relationships can be added to the ontology as necessary to describe the new data without requiring revision to previously modeled concepts. Because the ontology model is decoupled from the physical implementations of the data assets, all data in the organization can be equally represented by the ontology. This means any new data introduced into the organization\u2019s ecosystem can be integrated with the data fabric, regardless of its schema or source systems.<\/span><\/p>\n<p style=\"text-align: left;\"><span style=\"font-weight: 400;\">If our hypothetical e-commerce merchant began building or acquiring datasets with new fields such as customer email addresses, or even introduced entirely new domains such as supply chain management, the ontology could be readily extended so the data fabric could continue to support all data usage in the business without an expensive architectural overhaul.<\/span><\/p>\n<h3 style=\"text-align: left;\"><span style=\"font-weight: 400;\">Enable Granular Data Management<\/span><\/h3>\n<p style=\"text-align: left;\"><span style=\"font-weight: 400;\">Just as an ontology embeds human- and machine-readable meaning into the data model itself, it can also embed additional information about the data, including granular data management metadata about individual concepts. For example, the ontology might indicate that a phone number field is personally identifiable information (PII) so the data fabric would know to subject any dataset containing a phone number to stricter controls on access and use. Being able to operationalize security, privacy, and governance information at the data field level allows for extremely robust governance and can be used to enable enterprise-wide federation and data democratization while minimizing data privacy and security risks.<\/span><\/p>\n<h2 style=\"text-align: left;\"><span style=\"font-weight: 400;\">How Do You Get There?<\/span><\/h2>\n<p style=\"text-align: left;\"><span style=\"font-weight: 400;\">A data fabric is a powerful architectural tool for managing and utilizing the sprawl of data that occurs at modern organizations, but to realize its full potential it must be built on the semantic foundation of an enterprise ontology. Using an ontology will enable the data fabric to discover and operationalize connections among data, to integrate disparate and distributed data, and to enact robust and granular data governance.<\/span><\/p>\n<p style=\"text-align: left;\"><span style=\"font-weight: 400;\">At EK, we take a use case-driven, iterative approach to design and implementation, starting with a well-defined proof of concept that can rapidly demonstrate value and then scaling across the organization. These are some sample steps to achieve your first data fabric powered by an enterprise ontology:<\/span><\/p>\n<ul>\n<li style=\"text-align: left;\"><span style=\"font-weight: 400;\">Select a specific use case or domain to prioritize as a proof of concept;<\/span><\/li>\n<li style=\"text-align: left;\"><span style=\"font-weight: 400;\">Design and evaluate an enterprise architecture;<\/span><\/li>\n<li style=\"text-align: left;\"><span style=\"font-weight: 400;\">Inventory source data in the prioritized use case or domain;<\/span><\/li>\n<li style=\"text-align: left;\"><a href=\"https:\/\/enterprise-knowledge.com\/keys-to-successful-ontology-design\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\"><strong>Model entities, attributes, and relationships<\/strong><\/span><\/a><span style=\"font-weight: 400;\"> found in the source data to establish the ontology model;<\/span><\/li>\n<li style=\"text-align: left;\"><span style=\"font-weight: 400;\">Map the source data to the ontology to support the prototype data fabric; and<\/span><\/li>\n<li style=\"text-align: left;\"><span style=\"font-weight: 400;\">Create a plan to <\/span><strong><a href=\"https:\/\/enterprise-knowledge.com\/take-ai-beyond-a-prototype\/\" target=\"_blank\" rel=\"noopener\">scale the proof of concept<\/a><\/strong><span style=\"font-weight: 400;\"> to the entire organization.<\/span><\/li>\n<\/ul>\n<p>While data fabric is one of the most exciting new terms for enterprise data to emerge over the past few years and adoption of this architecture is on the rise, Enterprise Knowledge has a <strong><a href=\"https:\/\/enterprise-knowledge.com\/what-is-a-semantic-architecture-and-how-do-i-build-one\/\" target=\"_blank\" rel=\"noopener\">deep history of successfully empowering organizations with semantic data architectures<\/a><\/strong><span style=\"font-weight: 400;\">. We have drawn on this experience and expertise to successfully implement data fabrics for organizations in diverse industries and sectors, including <\/span><strong><a href=\"https:\/\/enterprise-knowledge.com\/building-a-semantic-enterprise-architecture\/\" target=\"_blank\" rel=\"noopener\">semantic layers to support scientific research<\/a><\/strong><span style=\"font-weight: 400;\">, <\/span><strong><a href=\"https:\/\/enterprise-knowledge.com\/a-course-recommendation-system-based-on-a-knowledge-graph\/\" target=\"_blank\" rel=\"noopener\">content recommenders for disparate digital learning materials<\/a><\/strong><span style=\"font-weight: 400;\">, and <\/span><strong><a href=\"https:\/\/enterprise-knowledge.com\/360-view-of-a-consumer-deduplicating-and-constructing-consumer-data-using-an-identity-graph\/\" target=\"_blank\" rel=\"noopener\">customer-360 and enterprise-360 views of integrated data<\/a><\/strong><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Are you ready to fully unlock the power of your organization\u2019s data? Want to know more about data fabrics, ontologies, and knowledge graphs? <\/span><strong><a href=\"https:\/\/enterprise-knowledge.com\/contact-us\/\" target=\"_blank\" rel=\"noopener\">Contact us here<\/a><\/strong><span style=\"font-weight: 400;\"> to take your first step toward a next-generation enterprise data ecosystem.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In today\u2019s rapidly growing and evolving data environment, it is increasingly difficult for organizations to get maximal value from the full breadth of their data. As more data is produced faster by more sources, it is difficult for analysts, data &hellip; <a href=\"https:\/\/enterprise-knowledge.com\/why-your-data-fabric-needs-an-enterprise-ontology\/\"  class=\"with-arrow\">Continue reading<\/a><\/p>\n","protected":false},"author":17,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"_uag_custom_page_level_css":"","footnotes":""},"categories":[512,184],"tags":[1070,697,236],"article-type":[100],"solution":[1111],"ppma_author":[1391],"class_list":["post-16030","post","type-post","status-publish","format-standard","hentry","category-knowledge-graphs-data-modeling","category-taxonomy-ontology-design","tag-data-fabric","tag-enterprise-ontology","tag-ontology","article-type-blog","solution-taxonomy-ontology"],"acf":[],"featured_image_urls_v2":{"full":"","thumbnail":"","medium":"","medium_large":"","large":"","1536x1536":"","2048x2048":"","slideshow":"","slideshow-2x":"","banner":"","home-large":"","home-medium":"","home-small":"","gform-image-choice-sm":"","gform-image-choice-md":"","gform-image-choice-lg":""},"post_excerpt_stackable_v2":"<p>In today\u2019s rapidly growing and evolving data environment, it is increasingly difficult for organizations to get maximal value from the full breadth of their data. As more data is produced faster by more sources, it is difficult for analysts, data scientists, and other consumers to be aware of and effectively use data being produced across organizational divisions and domain areas. Impaired discovery and use of data can lead to the direct costs of duplicated effort and wasted time, as well as the opportunity costs of unrealized data-driven insights. The concept of data fabric is increasingly recognized as a key solution&hellip;<\/p>\n","category_list_v2":"<a href=\"https:\/\/enterprise-knowledge.com\/category\/knowledge-graphs-data-modeling\/\" rel=\"category tag\">Knowledge Graphs &amp; Data Modeling<\/a>, <a href=\"https:\/\/enterprise-knowledge.com\/category\/taxonomy-ontology-design\/\" rel=\"category tag\">Taxonomy &amp; Ontology Design<\/a>","author_info_v2":{"name":"EK Team","url":"https:\/\/enterprise-knowledge.com\/author\/enterprise-knowledge\/"},"comments_num_v2":"0 comments","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Why Your Data Fabric Needs an Enterprise Ontology - Enterprise Knowledge<\/title>\n<meta name=\"description\" content=\"A data fabric is a key solution to modern data ecosystem challenges, and supporting it with an ontology amplifies its benefits.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/enterprise-knowledge.com\/why-your-data-fabric-needs-an-enterprise-ontology\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Why Your Data Fabric Needs an Enterprise Ontology - Enterprise Knowledge\" \/>\n<meta property=\"og:description\" content=\"A data fabric is a key solution to modern data ecosystem challenges, and supporting it with an ontology amplifies its benefits.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/enterprise-knowledge.com\/why-your-data-fabric-needs-an-enterprise-ontology\/\" \/>\n<meta property=\"og:site_name\" content=\"Enterprise Knowledge\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/Enterprise-Knowledge-359618484181651\/\" \/>\n<meta property=\"article:published_time\" content=\"2022-08-10T15:45:47+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-01-09T19:20:14+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/1-Ontology-Model-771x364.png\" \/>\n<meta name=\"author\" content=\"EK Team\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@EKConsulting\" \/>\n<meta name=\"twitter:site\" content=\"@EKConsulting\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"EK Team\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"7 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/enterprise-knowledge.com\/why-your-data-fabric-needs-an-enterprise-ontology\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/enterprise-knowledge.com\/why-your-data-fabric-needs-an-enterprise-ontology\/\"},\"author\":{\"name\":\"EK Team\",\"@id\":\"https:\/\/enterprise-knowledge.com\/#\/schema\/person\/fe4c950023b0a2d4ea9057f16c70a16c\"},\"headline\":\"Why Your Data Fabric Needs an Enterprise Ontology\",\"datePublished\":\"2022-08-10T15:45:47+00:00\",\"dateModified\":\"2024-01-09T19:20:14+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/enterprise-knowledge.com\/why-your-data-fabric-needs-an-enterprise-ontology\/\"},\"wordCount\":1431,\"publisher\":{\"@id\":\"https:\/\/enterprise-knowledge.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/enterprise-knowledge.com\/why-your-data-fabric-needs-an-enterprise-ontology\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/enterprise-knowledge.com\/wp-content\/uploads\/2022\/08\/1-Ontology-Model-771x364.png\",\"keywords\":[\"Data Fabric\",\"Enterprise Ontology\",\"Ontology\"],\"articleSection\":[\"Knowledge Graphs &amp; 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