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Snowflake","height":"200","src":"/adobe/dynamicmedia/deliver/dm-aid--c1cf5112-d351-40f4-9f2a-aa77a5228f6d/danielle-kucera.jpg?preferwebp=true&quality=85","lazyEnabled":true,"isLcpImage":false,"width":"200",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-74431c1855","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/danielle-kucera/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Danielle Kucera"}},{"authorImage":{"id":"image-e2c2408539","alt":"Shinji Kim, Principal Product Manager at Snowflake","height":"512","src":"/adobe/dynamicmedia/deliver/dm-aid--6eac4b6a-4c89-4721-95f1-96086125bee5/shinji-kim.png?preferwebp=true&quality=85","lazyEnabled":true,"isLcpImage":false,"width":"512",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-fdbb1fd15b","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/shinji-kim/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Shinji Kim"}}],"image":{"id":"image-9daddbb9a8","alt":"Diagram showing Business Ontology ensuring consistent business definitions","height":"856","src":"/adobe/dynamicmedia/deliver/dm-aid--bd15fdba-a8fc-4cf8-ba85-c10dd60c4f53/expedition-business-ontology.png?preferwebp=true&quality=85","lazyEnabled":true,"isLcpImage":false,"width":"2000",":type":"snowflake-site/components/image"},"timeToRead":"6","publicationDate":"NOV 03, 2026","tag":{"tagText":"Producto y tecnología","tagColor":"#3F808A"},"title":{"lines":["Business Ontology gobierna conceptos y métricas empresariales para IA y analíticas"],"type":"heading2",":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/blog/blog-hero"},"container":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-c50ecb50a3",":items":{},":itemsOrder":[],":type":"snowflake-site/components/container"},"button":{"id":"button-388b68c39c","showOutboundIcon":false,"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"UNKNOWN"}},":itemsOrder":["blog_hero","container","button"],":type":"snowflake-site/components/container"},"responsivegrid_content":{"columnCount":12,"columnClassNames":{"blog_title_2052300538":"aem-GridColumn aem-GridColumn--default--12","image":"aem-GridColumn aem-GridColumn--default--12","blog_text_650815874":"aem-GridColumn aem-GridColumn--default--12","blog_title_1682682914":"aem-GridColumn aem-GridColumn--default--12","image_333095280":"aem-GridColumn aem-GridColumn--default--12","blog_text_881009154":"aem-GridColumn aem-GridColumn--default--12","blog_text_1334654234":"aem-GridColumn aem-GridColumn--default--12","blog_text_598255608":"aem-GridColumn aem-GridColumn--default--12","blog_text_90895576":"aem-GridColumn aem-GridColumn--default--12","blog_title":"aem-GridColumn aem-GridColumn--default--12","blog_title_553216124":"aem-GridColumn aem-GridColumn--default--12","blog_title_922201594":"aem-GridColumn aem-GridColumn--default--12","blog_text_1060397060":"aem-GridColumn aem-GridColumn--default--12","blog_text_1329841915":"aem-GridColumn aem-GridColumn--default--12","blog_text":"aem-GridColumn aem-GridColumn--default--12","blog_text_64117581":"aem-GridColumn aem-GridColumn--default--12","blog_title_874620594":"aem-GridColumn aem-GridColumn--default--12","blog_title_382186722":"aem-GridColumn aem-GridColumn--default--12","quote_item":"aem-GridColumn aem-GridColumn--default--12","blog_text_1999528628":"aem-GridColumn aem-GridColumn--default--12","blog_title_1755654776":"aem-GridColumn aem-GridColumn--default--12","quote_item_189117634":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","appliedCssClassNames":"snowflake-layout-container-inner-padding-small",":items":{"blog_text":{"id":"blog-text-c7a9e7eff2","text":"\u003Cp\u003EHoy anunciamos \u003Ca target=\"_blank\" href=\"https://www.snowflake.com/en/product/features/horizon-context/\"\u003E\u003Cb\u003EBusiness Ontology\u003C/b\u003E \u003C/a\u003E(pronto en vista previa pública), una forma gobernada para que los equipos definan, gestionen y aprueben términos, entidades, relaciones y métricas empresariales compartidos, y los conecten con los datos y modelos que los implementan. Como parte de \u003Ca target=\"_blank\" href=\"https://www.snowflake.com/en/product/features/horizon/\"\u003ESnowflake Horizon Context\u003Cb\u003E,\u003C/b\u003E\u003C/a\u003E la capa de contexto gobernado de \u003Ca target=\"_blank\" href=\"https://www.snowflake.com/en/product/features/horizon/\"\u003EHorizon Catalog\u003C/a\u003E, Business Ontology proporciona a las personas y a los agentes de IA las mismas definiciones aprobadas, de modo que los agentes de IA puedan interpretar los datos empresariales como lo hace el negocio. Los equipos pueden reutilizar ese conocimiento en distintos agentes y aplicaciones sin tener que redefinirlo para cada herramienta, al tiempo que preservan las diferencias entre ámbitos como ventas, finanzas y marketing.\u003Cbr\u003E\r\n\u003Cbr\u003E\r\nPor ejemplo, un agente que responde a una pregunta sobre ingresos necesita saber cómo define finanzas el término “ingresos” y cómo se relaciona con los pedidos y los clientes. Ese conocimiento suele estar repartido entre modelos de BI, proyectos de dbt y la experiencia de quienes llevan mucho tiempo en la empresa, y los equipos suelen reconstruirlo para cada agente nuevo. Si un agente se equivoca, las personas toman decisiones basadas en una cifra incorrecta y pierden la confianza en las respuestas de la IA. Business Ontology ofrece a los equipos un único lugar oficial donde registrar ese conocimiento.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image":{"id":"image-da2213a2ad","alt":"Snowflake Business Ontology conecta conceptos empresariales como clientes, pedidos e ingresos netos con las tablas, vistas semánticas y servicios que los implementan, para que los agentes de todos los equipos trabajen con el mismo modelo de negocio.","height":"591","src":"/adobe/dynamicmedia/deliver/dm-aid--466e9231-d7e7-4cb6-8024-4c21c57d3f03/business-ontology-stack-diagram.png?preferwebp=true&quality=85","lazyEnabled":true,"isLcpImage":true,"width":"955","title":"Figura 1. Snowflake Business Ontology conecta conceptos empresariales como clientes, pedidos e ingresos netos con las tablas, vistas semánticas y servicios que los implementan, para que los agentes de todos los equipos trabajen con el mismo modelo de negocio.",":type":"snowflake-site/components/image"},"blog_title":{"id":"blog-title-d944e9b04d","propertiesId":"crea-un-contexto-de-negocio-fiable-con-la-integracion-de-conocimientos-de-todo-tu-patrimonio-de-datos","type":"heading2","lines":["Crea un contexto de negocio fiable con la integración de conocimientos de todo tu patrimonio de datos"],":type":"snowflake-site/components/blog/blog-title","appliedCssClassNames":"left-alignment"},"blog_text_1060397060":{"id":"blog-text-8da40fdf5b","text":"\u003Cp\u003EHorizon Context reúne el conocimiento de las herramientas que los equipos ya utilizan. Sus conectores de metadatos listos para usar recopilan esquemas, registros de consultas, definiciones de paneles de control y señales de uso de fuentes como Tableau, Power BI, dbt, SQL Server, Sigma, Omni y PostgreSQL. A continuación, el linaje multiplataforma rastrea los datos desde una base de datos de origen, pasando por las transformaciones, hasta el panel de control que los muestra. El resultado es una vista conectada de tu patrimonio de datos que permite a los equipos comprender mejor de dónde proceden los datos y cómo se utilizan, tanto dentro como fuera de Snowflake.\u003C/p\u003E\r\n\u003Cp\u003EPara convertirlo en algo en lo que los agentes puedan confiar, Snowflake ofrece tres capas de contexto, cada una con una función distinta: \u003Ca href=\"https://www.snowflake.com/es/blog/enterprise-ai-agents-grounded-context/\" target=\"_blank\"\u003ESnowflake Cortex Sense\u003C/a\u003E (pronto en vista previa pública) infiere el contexto automáticamente, Business Ontology gobierna el significado empresarial y las \u003Ca href=\"https://docs.snowflake.com/en/user-guide/views-semantic/overview\" target=\"_blank\"\u003Evistas semánticas de Snowflake\u003C/a\u003E ejecutan las métricas. \u003C/p\u003E\r\n\u003Cp\u003E¿Por qué tres capas en lugar de una? Porque cada una aborda un problema diferente y ninguna capa por sí sola puede resolver bien los tres. Cortex Sense proporciona de inmediato a los agentes una amplia cobertura de los patrimonios de datos, sin que tu equipo tenga que definir primero a mano cada tabla y métrica. Business Ontology aporta autoridad donde más importa, para que las personas y los agentes trabajen con significados empresariales aprobados. Las vistas semánticas aportan precisión para que cada métrica se calcule siempre de la misma manera. \u003C/p\u003E\r\n\u003Cp\u003ELas capas no son secuenciales: Los clientes pueden empezar por la capa que resuelva su problema más urgente y añadir las demás a medida que crezcan. Algunos equipos pueden empezar por sus necesidades de glosario; otros, por las métricas ejecutables. Sea cual sea el punto de partida, las tres capas proporcionan a cada agente, aplicación y persona un contexto de negocio coherente y fiable.\u003C/p\u003E\r\n\u003Cp\u003EVeamos cada una en detalle.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"blog_title_2052300538":{"id":"blog-title-5dd670cba2","propertiesId":"automatiza-el-contexto-con-cortex-sense","type":"heading2","lines":["Automatiza el contexto con Cortex Sense"],":type":"snowflake-site/components/blog/blog-title","appliedCssClassNames":"left-alignment"},"blog_text_64117581":{"id":"blog-text-7c908bcaae","text":"\u003Cp\u003EPara muchos equipos, Cortex Sense es el punto de partida natural porque se encarga de gran parte del trabajo en segundo plano. Recopila contexto a medida que las personas consultan datos, crean paneles de control y ejecutan pipelines, y convierte el trabajo cotidiano en conocimiento del negocio, reduciendo el tiempo dedicado a definir qué significa cada tabla y métrica y cómo se conectan.\u003C/p\u003E\n\u003Cp\u003ECortex Sense lo consigue creando contexto a partir de los metadatos y patrones de uso que los equipos ya generan, incluidos el historial de consultas, los paneles de control y los modelos de dbt. A medida que cambia el negocio, ese conocimiento se mantiene al día, ya que Cortex Sense lo actualiza automáticamente con la frecuencia que elijas. Los equipos delimitan un caso de uso de negocio, conectan el contexto existente pertinente y lo perfeccionan mediante comentarios y evaluaciones, lo que reduce la necesidad de modelar manualmente cada tabla. Cortex Sense identifica de forma inteligente los conocimientos contradictorios y pregunta a los equipos en qué fuente deben confiar.\u003C/p\u003E\n\u003Cp\u003ECuando los equipos están preparados para gobernar sus términos más importantes, Cortex Sense puede crear un borrador inicial en Business Ontology con propuestas de definiciones, relaciones y vínculos a los datos, para que nadie tenga que empezar desde cero. Los equipos pueden delimitar un caso de uso de negocio, conectar el contexto existente pertinente y perfeccionarlo mediante comentarios y evaluaciones, lo que reduce la necesidad de modelar manualmente cada tabla. Cortex Sense identifica de forma inteligente los conocimientos contradictorios y pregunta a los equipos en qué fuente deben confiar.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"blog_title_553216124":{"id":"blog-title-f63eb73d76","propertiesId":"define-el-contexto-de-negocio-con-business-ontology","type":"heading2","lines":["Define el contexto de negocio con Business Ontology"],":type":"snowflake-site/components/blog/blog-title","appliedCssClassNames":"left-alignment"},"blog_text_1999528628":{"id":"blog-text-9c9d5d6980","text":"\u003Cp\u003EBusiness Ontology es el lugar donde los equipos registran qué significan sus términos de negocio más importantes, quién es responsable de ellos y cómo se relacionan. Tomemos como ejemplo los “ingresos netos”. En lugar de que cada vista semántica, panel de control y agente tenga su propia versión, un analista los define una vez —o los importa de un glosario existente—, establece su ámbito como “finanzas”, designa a una persona responsable, consigue su aprobación y los vincula a la métrica de la vista semántica que los calcula (consulta la figura 2). A partir de ese momento, los agentes y los demás equipos trabajan con esa definición aprobada. Los equipos pueden:\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EBasar los agentes en conceptos empresariales:\u003C/b\u003E Los expertos en cada ámbito definen conceptos como clientes, pedidos e ingresos —y cómo se relacionan—, y los ingenieros conectan esas definiciones con los datos. Así, los agentes interpretan los datos a partir del conocimiento propio del negocio. \u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EAlinear las métricas entre las vistas semánticas: \u003C/b\u003ELos equipos vinculan métricas equivalentes de sus propias vistas semánticas a una definición de negocio compartida, alineando su significado sin obligar a todos los equipos a adoptar una única implementación. También se mantienen las diferencias intencionadas: una empresa de restauración podría definir de forma distinta las ventas en establecimientos comparables para cada marca, con cada versión aprobada por separado, etiquetada con su propia marca y vinculada a la vista semántica que la calcula.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EAyudar a todos a encontrar la definición adecuada: \u003C/b\u003ECualquiera puede buscar un término, consultar quién es responsable de él y si está aprobado, y acceder al lugar donde se calcula. Las variantes regionales y de cada marca conservan su ámbito.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_333095280":{"id":"image-4bf7000702","alt":"En Business Ontology, los ingresos netos tienen una única definición aprobada, con sus sinónimos, conceptos relacionados y variantes, vinculada a las métricas que los calculan en dos vistas semánticas.","height":"1049","src":"/adobe/dynamicmedia/deliver/dm-aid--c1bb083f-921d-470e-bd5c-76a49b576b02/business-ontology-ui.png?preferwebp=true&quality=85","lazyEnabled":true,"isLcpImage":false,"width":"2048","title":"Figura 2. En Business Ontology, los ingresos netos tienen una única definición aprobada, con sus sinónimos, conceptos relacionados y variantes, vinculada a las métricas que los calculan en dos vistas semánticas.",":type":"snowflake-site/components/image"},"blog_text_1334654234":{"id":"blog-text-b70949815f","text":"\u003Cp\u003E \u003C/p\u003E\r\n\u003Cp\u003EComo estas definiciones influyen en las decisiones, las organizaciones controlan quién puede crearlas, editarlas y aprobarlas mediante los controles de gobernanza de Horizon Catalog. Las sugerencias de IA y las definiciones importadas son un punto de partida para la revisión, y las personas responsables deciden cuáles se convierten en oficiales. Cuando una definición aprobada entra en conflicto con algo que Cortex Sense ha inferido, los agentes utilizan la definición aprobada y Cortex Sense aprende de ella.\u003C/p\u003E\r\n\u003Cp\u003E \u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item":{"id":"quote-item-aa63bc93c3","alignment":"left","layout":"card","quoteSourceName":"Joe Tobey","quoteSourceTitle":"Head of Data Product Engineering, dentsu","showQuoteIcon":true,"quote":"“Business Ontology asigna a cada definición un responsable, la vincula a los datos que la implementan y la convierte en la respuesta que da cada agente. Como primeros en adoptar el producto, esto es lo que nos permite poner agentes a trabajar con nuestros datos con total confianza”.","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_title_382186722":{"id":"blog-title-0e93f3bde4","propertiesId":"aplica-las-definiciones-y-la-logica-una-sola-vez-con-vistas-semanticas","type":"heading2","lines":["Aplica las definiciones y la lógica una sola vez con vistas semánticas"],":type":"snowflake-site/components/blog/blog-title","appliedCssClassNames":"left-alignment"},"blog_text_881009154":{"id":"blog-text-35c54d1b2c","text":"\u003Cp\u003ELas vistas semánticas definen cómo se calcula cada métrica, mientras que Business Ontology gobierna qué significa y quién la ha aprobado. Cada vista agrupa las métricas, dimensiones y uniones de un ámbito en un objeto de Snowflake que los agentes, las herramientas de BI y SQL pueden consultar directamente, de modo que los agentes generan SQL a partir de una lógica gobernada en vez de intentar deducirla. Business Ontology vincula las definiciones aprobadas a las vistas semánticas que las calculan, pero no modifica el cálculo. Esa responsabilidad sigue correspondiendo a los propietarios de cada vista.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"blog_title_922201594":{"id":"blog-title-0b3bf805d2","propertiesId":"un-contexto-de-calidad-requiere-una-plataforma-abierta-por-diseno","type":"heading2","lines":["Un contexto de calidad requiere una plataforma abierta por diseño"],":type":"snowflake-site/components/blog/blog-title","appliedCssClassNames":"left-alignment"},"blog_text_598255608":{"id":"blog-text-7dacdc770f","text":"\u003Cp\u003EEl conocimiento del negocio solo resulta útil si puede evolucionar con él. Por eso Snowflake ayudó a fundar \u003Ca href=\"https://www.snowflake.com/es/blog/apache-ossie-open-semantic-interchange-incubator/\" target=\"_blank\"\u003EApache Ossie (en incubación)\u003C/a\u003E, el estándar abierto y neutral con respecto a los proveedores para modelos semánticos, que ya cuenta con el respaldo de decenas de organizaciones, entre ellas Microsoft, Salesforce, dbt Labs, Qlik y ThoughtSpot. Las vistas semánticas pueden importar y exportar definiciones de Ossie, de modo que las métricas pueden trasladarse entre Snowflake y otras herramientas compatibles con Ossie en lugar de tener que reconstruirse en cada una de ellas. Los agentes externos a Snowflake también pueden consultar vistas semánticas mediante el Protocolo de contexto de modelo (MCP), mientras Horizon Catalog gobierna el acceso.\u003C/p\u003E\r\n\u003Cp\u003E \u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item_189117634":{"id":"quote-item-52572dd129","alignment":"left","layout":"card","quoteSourceName":"Morten Lileng","quoteSourceTitle":"Global Head of Engineering, dentsu","showQuoteIcon":true,"quote":"“La deriva semántica es uno de los riesgos más infravalorados en los entornos de datos con múltiples socios, y en Merkle, la agencia de datos y tecnología de dentsu, trabajamos en algunos de los más complejos del sector. Business Ontology de Snowflake resuelve ese problema desde la propia infraestructura: asigna un responsable a cada definición y ofrece una única respuesta gobernada a todos los sistemas posteriores”.","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_title_874620594":{"id":"blog-title-c8e61a1518","propertiesId":"que-dicen-las-empresas-de-analiticas-sobre-snowflake-business-ontology","type":"heading2","lines":["Qué dicen las empresas de analíticas sobre Snowflake Business Ontology"],":type":"snowflake-site/components/blog/blog-title","appliedCssClassNames":"left-alignment"},"blog_text_650815874":{"id":"blog-text-a749eac28d","text":"\u003Cp\u003EMuchas personas utilizan herramientas de BI y analíticas para obtener respuestas a sus preguntas, por lo que contar con un contexto de negocio coherente es fundamental. Así ven Omni, Sigma y ThoughtSpot el reto del contexto y el papel que desempeña Business Ontology para abordarlo:\u003C/p\u003E\r\n\u003Ch4\u003EOmni\u003C/h4\u003E\r\n\u003Cp\u003E“Piensa en el contexto como en la incorporación de un nuevo analista: es todo lo que le enseñarías para que sepa cuándo, por qué y cómo utilizar cada elemento. \u003Ca target=\"_blank\" href=\"http://omni.co\"\u003EOmni\u003C/a\u003E se creó en torno a un modelo semántico gobernado y ofrece la única integración bidireccional con las vistas semánticas de Snowflake. Ahora, Business Ontology lleva esa base aún más lejos al capturar definiciones de negocio aprobadas. Juntos, ayudamos a nuestros clientes comunes a crear un contexto fiable que pueda servir a todos los usuarios y agentes”. \u003C/p\u003E\r\n\u003Cp\u003E— Jamie Davidson, Co-founder and President de Omni\u003C/p\u003E\r\n\u003Ch4\u003ESigma\u003C/h4\u003E\r\n\u003Cp\u003E“Los agentes de IA solo son tan fiables como el contexto y las definiciones de negocio que los sustentan. Con Business Ontology, nuestros clientes comunes pueden definir sus conceptos empresariales una sola vez y reutilizarlos sin complicaciones en \u003Ca target=\"_blank\" href=\"https://www.sigmacomputing.com/product/ai\"\u003ESigma AI \u003C/a\u003Epara crear aplicaciones, paneles de control y agentes gobernados, y ofrecer analíticas fiables en Sigma”.\u003Cbr\u003E\r\n— Zalak Trivedi, Director of Product Management de Sigma \u003C/p\u003E\r\n\u003Ch4\u003EThoughtSpot\u003C/h4\u003E\r\n\u003Cp\u003E“Una IA fiable depende de un contexto de negocio fiable. Snowflake Business Ontology ofrece a las empresas un espacio gobernado para definir el significado de sus términos de negocio, y ThoughtSpot amplía continuamente ese contexto con el conocimiento de los usuarios empresariales capturado mediante \u003Ca target=\"_blank\" href=\"https://www.thoughtspot.com/product/agents/spotter\"\u003ESpotter\u003C/a\u003E, lo que proporciona respuestas y acciones precisas y explicables para cada usuario. Juntos, ayudamos a los clientes a ampliar con confianza las analíticas agénticas”.\u003C/p\u003E\r\n\u003Cp\u003E— Francois Lopitaux, Senior Vice President of Product de ThoughtSpot\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"blog_title_1682682914":{"id":"blog-title-aaa30a3c69","propertiesId":"convierte-el-conocimiento-en-un-activo-empresarial-coherente-con-business-ontology","type":"heading2","lines":["Convierte el conocimiento en un activo empresarial coherente con Business Ontology"],":type":"snowflake-site/components/blog/blog-title","appliedCssClassNames":"left-alignment"},"blog_text_90895576":{"id":"blog-text-54931bf201","text":"\u003Cp\u003ELas personas cambian de puesto, las herramientas se sustituyen y los modelos de datos evolucionan. Con demasiada frecuencia, el conocimiento que hay detrás se pierde por el camino. Business Ontology convierte ese conocimiento en un activo duradero para la empresa, con una persona responsable y un vínculo claro al lugar donde se calcula cada definición. Cada nuevo agente o aplicación puede partir de lo que el negocio ya sabe.\u003C/p\u003E\n\u003Cp\u003ESi quieres profundizar en Business Ontology, \u003Ca target=\"_blank\" href=\"https://www.snowflake.com/en/webinars/virtual-hands-on-lab/get-hands-on-with-snowflake-context--how-business-ontology-gives/?utm_source=expeditionams27&utm_medium=event&utm_campaign=na-en-event&utm_content=-vhol-get-hands-on-with-snowflake-context\"\u003Econsulta nuestro laboratorio práctico\u003C/a\u003E y lee nuestra entrada de blog \u003Ca target=\"_blank\" href=\"https://www.snowflake.com/en/blog/engineering/business-ontology-context/\"\u003E“El significado antes que las métricas: cómo creamos una Business Ontology gobernada para agentes de IA”.\u003C/a\u003E\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"blog_title_1755654776":{"id":"blog-title-c5730194ce","propertiesId":"preguntas-frecuentes","type":"heading2","lines":["Preguntas frecuentes"],":type":"snowflake-site/components/blog/blog-title","appliedCssClassNames":"left-alignment"},"blog_text_1329841915":{"id":"blog-text-5116ad1270","text":"\u003Ch4\u003E¿Qué es Snowflake Business Ontology?\u003C/h4\u003E\n\u003Cp\u003EBusiness Ontology (próximamente en vista previa pública) es una capa de modelado y gobernanza de negocio de Snowflake Horizon Context. Las organizaciones pueden utilizarla para definir conceptos y métricas empresariales, así como las relaciones entre ellos, con independencia de cualquier modelo de datos concreto. Cada definición registra quién es responsable de ella y su estado de aprobación, y se vincula a las vistas semánticas, tablas y vistas que la implementan. Solo se proporcionan definiciones aprobadas a los agentes de IA de Snowflake CoCo y Snowflake CoWork, por lo que estos trabajan con el significado que respalda la organización en lugar de elegir entre implementaciones rivales.\u003C/p\u003E\n\u003Ch4\u003E¿Por qué necesitan contexto de negocio los agentes de IA?\u003C/h4\u003E\n\u003Cp\u003EEl contexto de negocio gobernado ayuda a los agentes a interpretar los datos como lo hace el negocio para que puedan ofrecer respuestas más precisas. Los agentes de IA pueden acceder a los datos, pero no “entienden” automáticamente qué significan los términos empresariales ni cómo se relacionan los conceptos. Necesitan contexto: referencias aprobadas que les indiquen en qué definición confiar, qué políticas seguir y qué conocimiento corporativo incorporar. Sin ese contexto, los agentes hacen suposiciones sobre los significados y las fuentes de datos pertinentes, y pueden dar respuestas distintas a la misma pregunta. \u003C/p\u003E\n\u003Ch4\u003E¿En qué se diferencia Business Ontology de las vistas semánticas?\u003C/h4\u003E\n\u003Cp\u003EBusiness Ontology define qué significa un término empresarial, quién es su responsable y cómo se relaciona con otros conceptos. Las vistas semánticas definen cómo se calcula cada métrica y agrupan métricas, dimensiones y uniones en objetos que los agentes, las herramientas de BI y SQL pueden consultar directamente. Business Ontology vincula las métricas equivalentes de distintas vistas semánticas a una única definición compartida y aprobada.\u003C/p\u003E\n\u003Ch4\u003E¿Se pueden trasladar las definiciones empresariales entre Snowflake y otras herramientas?\u003C/h4\u003E\n\u003Cp\u003ESí. Business Ontology puede importar y exportar conceptos, definiciones y relaciones empresariales a formatos abiertos, como Apache Ossie (en incubación) y Resource Description Framework (RDF), para que los equipos puedan reutilizar el conocimiento empresarial aprobado en otras herramientas en lugar de volver a definirlo. Las vistas semánticas también pueden importar y exportar definiciones de Ossie, por lo que no es necesario volver a crear las métricas. Los agentes externos a Snowflake pueden consultar las vistas semánticas mediante MCP, mientras Horizon Catalog gobierna el acceso.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text","image","blog_title","blog_text_1060397060","blog_title_2052300538","blog_text_64117581","blog_title_553216124","blog_text_1999528628","image_333095280","blog_text_1334654234","quote_item","blog_title_382186722","blog_text_881009154","blog_title_922201594","blog_text_598255608","quote_item_189117634","blog_title_874620594","blog_text_650815874","blog_title_1682682914","blog_text_90895576","blog_title_1755654776","blog_text_1329841915"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"columnCount":12,"columnClassNames":{},"gridClassNames":"aem-Grid aem-Grid--12 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un contexto de negocio fiable con la integración de conocimientos de todo tu patrimonio de datos","level":"h2","anchorId":"#crea-un-contexto-de-negocio-fiable-con-la-integracion-de-conocimientos-de-todo-tu-patrimonio-de-datos","hierarchicalChildrenStructure":[]},{"headingText":"Automatiza el contexto con Cortex Sense","level":"h2","anchorId":"#automatiza-el-contexto-con-cortex-sense","hierarchicalChildrenStructure":[]},{"headingText":"Define el contexto de negocio con Business Ontology","level":"h2","anchorId":"#define-el-contexto-de-negocio-con-business-ontology","hierarchicalChildrenStructure":[]},{"headingText":"Aplica las definiciones y la lógica una sola vez con vistas semánticas","level":"h2","anchorId":"#aplica-las-definiciones-y-la-logica-una-sola-vez-con-vistas-semanticas","hierarchicalChildrenStructure":[]},{"headingText":"Un contexto de calidad requiere una plataforma abierta por 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