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2025","image":{"id":"image-48ba1404df","lazyEnabled":true,"alt":"Digital illustration of a ring of icons representing elements of data mesh, including security, privacy, discoverability and more.","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--e2b7a9f3-afe8-44fd-a497-a6b6de02290d/data-mesh-demo-recap-blogheader-1680x720.png?preferwebp=true&quality=85","height":"720","width":"1680",":type":"snowflake-site/components/image"},"authors":[{"authorImage":{"id":"image-d55c8e9579","lazyEnabled":true,"alt":"Headshot-style photo of Jenna Roering","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--14e99beb-668f-4cb1-9884-2a9fecb1e021/jenna-roering.png?preferwebp=true&quality=85","height":"512","width":"512",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-b30086f55f","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/jenna-roering/"},"linkTargetContentType":"DOCUMENT_LEARN","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Jenna Roering"}},{"authorImage":{"id":"image-a4b648fef5","lazyEnabled":true,"alt":"Matthias Nicola","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--448628d1-4404-47d5-bf58-d8ee8c195da5/matthias-nicola.jpg?preferwebp=true&quality=85","height":"200","width":"200",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-851122a8e4","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/matthias-nicola/"},"linkTargetContentType":"DOCUMENT_LEARN","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Matthias Nicola"}}],"tag":{"tagText":"Producto y tecnología","tagColor":"#3F808A"},"title":{"lines":["Resumen de la demo de data mesh: eliminar silos de datos con Internal Marketplace"],"type":"heading2",":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/blog/blog-hero"}},":itemsOrder":["blog_hero"],":type":"snowflake-site/components/container"},"responsivegrid_content":{"columnClassNames":{"blog_text_424278392":"aem-GridColumn aem-GridColumn--default--12","blog_text_1320022733":"aem-GridColumn aem-GridColumn--default--12","image":"aem-GridColumn aem-GridColumn--default--12","blog_text":"aem-GridColumn aem-GridColumn--default--12","image_209205566":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnCount":12,"appliedCssClassNames":"snowflake-layout-container-inner-padding-small",":items":{"blog_text":{"id":"blog-text-a942372827","text":"\u003Cp\u003E\u003Ci\u003ENota: Este blog fue actualizado el 9 de julio de 2025.\u003C/i\u003E\u003C/p\u003E\n\u003Cp\u003EEl data mesh ha ganado terreno en los últimos años, impulsado por su promesa de reducir la carga sobre los equipos de datos centralizados mediante la eliminación de cuellos de botella, el escalado de la gestión de datos y la aceleración del tiempo de valorización de los datos. Para quienes aún no se han sumado a esta tendencia, el \u003Ca href=\"https://www.snowflake.com/es/fundamentals/data-mesh-for-self-service-data/\" target=\"_blank\"\u003Edata mesh\u003C/a\u003E es un enfoque sociotécnico que hace hincapié en la propiedad descentralizada de los datos por dominio y en el tratamiento de los datos como un producto, posibilitado por una infraestructura de datos de autoservicio. Su objetivo es abordar los desafíos del escalado de la gestión de datos, el acceso y el data sharing ante el aumento continuo de fuentes de datos y consumidores. \u003C/p\u003E\n\u003Cp\u003EEl experto en data mesh, Matthias Nicola, ha guiado a numerosos clientes de Snowflake en la exploración, creación y operación de arquitecturas de data mesh. Estas iniciativas le han dado una perspectiva única sobre el atractivo del data mesh como arquitectura técnica y como enfoque organizativo. En esta entrada de blog, repasaremos los aspectos más destacados de nuestro reciente \u003Ca href=\"https://www.snowflake.com/webinars/product-demo/data-mesh-demo-how-to-build-and-govern-your-data-products-in-snowflake-2025-04-29/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Ewebinar de demostración de data mesh\u003C/a\u003E, en el que Matthias analizó el potencial del data mesh para transformar las empresas y profundizó en las soluciones de Snowflake, incluido Internal Marketplace, para mostrar cómo pueden capacitar a tu organización para compartir datos gobernados y documentados como productos de datos entre unidades de negocio. Aunque el data mesh también está sujeto a importantes consideraciones organizativas, este webinar se centró en las capacidades de la plataforma de datos para la gestión de productos de datos.\u003C/p\u003E\n\u003Ch2\u003EEl dilema de los datos: por qué los enfoques tradicionales se quedan cortos \u003C/h2\u003E\n\u003Cp\u003ELos equipos de gestión de datos centralizados tradicionales a menudo no pueden hacer frente a la interminable acumulación de solicitudes de datos. Esto genera cuellos de botella que dificultan la capacidad de una empresa para escalar y adaptarse a las necesidades de datos en constante evolución de su negocio. Además, los equipos centrales tienen dificultades por la falta de conocimiento del dominio (en marketing, producto, ventas y otras unidades de negocio), lo que provoca retrasos en la entrega de los datos correctos a los consumidores de datos adecuados. Cada uno de estos obstáculos ralentiza a los equipos e impacta negativamente en la colaboración de datos, lo que se traduce en un mayor tiempo de valorización y una menor agilidad de datos. \u003C/p\u003E\n\u003Ch2\u003ESoluciones de Snowflake: capacidades clave para el éxito del data mesh \u003C/h2\u003E\n\u003Cp\u003EPara superar estos desafíos, muchas empresas con visión de futuro están adoptando un enfoque de data mesh para reducir los cuellos de botella organizativos y las limitaciones de la gestión de datos centralizada tradicional. La arquitectura de data mesh ofrece el potencial de un enfoque más ágil y escalable para la gestión de datos, proporcionando a los equipos mayor autonomía y un data sharing fluido. \u003C/p\u003E\n\u003Cp\u003ELos cuatro principios clave de un data mesh son la gobernanza federada, la propiedad y arquitectura centradas en el dominio, los datos como producto y la infraestructura de autoservicio. \u003C/p\u003E\n\u003Cp\u003ELa plataforma de Snowflake ofrece soluciones y capacidades que se alinean con los principios del data mesh, entre ellas:   \u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EGobernanza federada: \u003C/b\u003ECapacita a las organizaciones con sólidas funciones de gobernanza, disponibles a través de Snowflake \u003Ca href=\"https://www.snowflake.com/en/product/features/horizon/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EHorizon \u003C/a\u003ECatalog, para controlar el acceso, supervisar el uso y aplicar políticas de seguridad de forma coherente en distintos dominios y entornos.  \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EPropiedad centrada en el dominio: \u003C/b\u003ELa arquitectura distribuida y multinube de Snowflake apoya la propiedad centrada en el dominio al proporcionar entornos independientes para cada dominio. Esto fomenta la independencia a la vez que permite un data sharing y una colaboración fluidos entre dominios. \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EDatos como producto: \u003C/b\u003EPermite a los dominios empaquetar objetos de datos, metadatos y políticas de gobernanza como productos de datos que pueden publicarse y descubrirse fácilmente en Snowflake \u003Ca href=\"https://docs.snowflake.com/en/user-guide/collaboration/listings/organizational/org-listing-about#the-internal-marketplace\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EInternal Marketplace\u003C/a\u003E, lo que garantiza que activos de datos fiables y de alta calidad sean fácilmente accesibles. Los productos de datos en Snowflake también pueden incluir activos de datos almacenados y gestionados fuera de Snowflake.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cb\u003EInfraestructura de autoservicio: \u003C/b\u003ELa facilidad de uso de Snowflake y su interoperabilidad con fuentes externas simplifican el acceso a los datos y capacitan a los equipos para operar de forma independiente, reduciendo la dependencia de los equipos centrales y fomentando una verdadera infraestructura de datos de autoservicio.\u003C/li\u003E\n\u003C/ul\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image":{"id":"image-9344efeb47","lazyEnabled":true,"alt":"Chart of 4 columns showing Snowflake capabilities for 4 tenants of data mesh: federated governance, domain-centric ownership and architecture, data as a product, self-service infrastructure","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--2de9e00d-cf12-4ed3-b004-e42dcdfeca62/snowflakedatamesh-capabilities.jpg?preferwebp=true&quality=85","height":"610","width":"1760","title":"Las soluciones de Snowflake están alineadas con los principios fundamentales de data mesh",":type":"snowflake-site/components/image"},"blog_text_424278392":{"id":"blog-text-5aacaea8f0","text":"\u003Cp\u003EEstas capacidades proporcionan la base esencial para construir y operar una arquitectura de data mesh con éxito. \u003C/p\u003E\n\u003Cp\u003EAl agilizar el data sharing entre distintos dominios, muchas organizaciones están eliminando eficazmente los silos de datos tradicionales y promoviendo un ecosistema de datos más integrado. Snowflake ayuda a organizaciones como FlixBus, líder mundial en tecnología para el sector de los viajes, a aprovechar plenamente los beneficios transformadores del data mesh. FlixBus implementó una arquitectura de data mesh y aprovechó Snowflake Internal Marketplace y los \u003Ca href=\"https://other-docs.snowflake.com/en/collaboration/collaboration-listings-about#what-is-a-listing\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Eproductos de datos\u003C/a\u003E, un método para empaquetar información con metadatos, descripción y más como un producto de datos. A partir de ahí, FlixBus pudo compartir y movilizar sus datos para mejorar las operaciones de la flota, prever la oferta y la demanda, medir el rendimiento del negocio y ofrecer analíticas de autoservicio. \u003C/p\u003E\n\u003Ch2\u003ECómo alcanzar el éxito con data mesh en Snowflake: respuestas a tus principales preguntas \u003C/h2\u003E\n\u003Cp\u003EEl data mesh puede parecer complejo al principio, pero no tiene por qué serlo. Durante este webinar en directo, los asistentes mostraron un gran interés por profundizar en aspectos específicos de las implementaciones de data mesh con Snowflake. Para ofrecer claridad y orientación, hemos recopilado las preguntas que generaron mayor interés: \u003C/p\u003E\n\u003Ch3\u003EP: ¿Cómo elijo entre una cuenta única o varias cuentas de Snowflake en la arquitectura de data mesh?\u003C/h3\u003E\n\u003Cp\u003ELa decisión de usar una cuenta única o varias cuentas de Snowflake depende en gran medida de las necesidades específicas, los desafíos o los requisitos legales de tu organización. Algunos aspectos a tener en cuenta para determinar si optar por una cuenta única o por varias cuentas son: \u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003ESi necesitas o no el máximo aislamiento entre dominios de negocio, por razones legales o de seguridad, con configuraciones de seguridad y gestión de usuarios independientes por dominio.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003ELas regiones en las que opera tu organización: ¿operas a nivel internacional con varias empresas (equipos distribuidos en regiones como Asia, EE. UU. o Europa)? ¿o tu organización opera en una única región geográfica?  \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003ELas unidades de negocio que trabajan en diferentes plataformas en la nube (AWS, Google Cloud, Azure) en distintas regiones deben tener en cuenta también los requisitos de localización. Además, ¿tienes requisitos de seguridad o legales que abarquen varias nubes y regiones? \u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cp\u003ETambién se deben tener en cuenta aspectos como la medición y el control de costes, así como la posibilidad de que los equipos configuren la seguridad. Algunas organizaciones optan por usar una sola cuenta porque es más sencilla y fácil de gestionar. Sin embargo, otras prefieren varias cuentas para garantizar una mayor privacidad, dar cabida a un conjunto más amplio de regiones y nubes, y satisfacer necesidades de seguridad específicas. Independientemente de si se utiliza una única cuenta o varias cuentas, se recomienda utilizar una cuenta organizativa para crear y gestionar fácilmente perfiles de dominio (también conocidos como \u003Ca href=\"https://docs.snowflake.com/en/user-guide/collaboration/organization-profiles/org-profile-manage\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Eperfiles organizativos\u003C/a\u003E).\u003C/p\u003E\n\u003Cp\u003ESea cual sea tu elección, una cuenta o varias, ten en cuenta que no estás vinculado a ninguna opción, ya que el Internal Marketplace de Snowflake funciona sin problemas en una o más cuentas y en topologías de cuentas en evolución, como se muestra en la imagen inferior.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_209205566":{"id":"image-ee9e87da49","lazyEnabled":true,"alt":"Diagram showing how Internal Marketplace can span domains in multiple Snowflake accounts.","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--b6dc0241-aece-4411-a3e2-f076ffd6a76a/datamesh-internalmarketplace.png?preferwebp=true&quality=85","height":"949","width":"1600","title":"Snowflake Internal Marketplace funciona sin problemas en una o más cuentas y en topologías de cuentas en constante evolución.",":type":"snowflake-site/components/image"},"blog_text_1320022733":{"id":"blog-text-520cfa831f","text":"\u003Cp\u003EConsulta \u003Ca href=\"https://www.phdata.io/blog/how-many-snowflake-accounts-should-i-have/#:~:text=Managing%20a%20single%20Snowflake%20account,and%20businesses%20new%20to%20Snowflake.%20%20https://medium.com/snowflake/designing-your-snowflake-topology-b9407c3e36f8\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Eeste artículo para saber más\u003C/a\u003E.   \u003C/p\u003E\n\u003Ch3\u003EP: ¿Cómo puedo configurar perfiles de dominio?\u003C/h3\u003E\n\u003Cp\u003EComo administrador de la organización, puedes configurar perfiles de dominio mediante \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/commands-organization-profiles\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EOrganization Profiles\u003C/a\u003E en el Internal Marketplace. Los perfiles de organización son objetos de Snowflake estándar que puedes crear, modificar, eliminar y mostrar, y que sirven para listar información sobre el origen y la propiedad de los datos. Para crear o modificar un perfil se utiliza un archivo YAML como entrada, que contiene el nombre del dominio, una descripción y varios atributos del dominio, como información de contacto o un aprobador predeterminado para las solicitudes de productos de datos. Esto ayuda a establecer una propiedad y una procedencia de los datos claras para fomentar la confianza, la calidad y la estructura de los datos, al tiempo que se refuerza la gobernanza en toda la organización. \u003C/p\u003E\n\u003Ch3\u003EP: ¿Qué tipos de objetos puede contener un producto de datos en Snowflake?\u003C/h3\u003E\n\u003Cp\u003EUn producto de datos puede contener uno o más objetos de distintos tipos, entre ellos: \u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003EBases de datos\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EEsquemas\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003ETablas\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003ETablas dinámicas\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003ETablas externas\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EDatos semiestructurados, como JSON y XML\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EArchivos y documentos no estructurados, aunque estén almacenados en contenedores de almacenamiento fuera de Snowflake\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003ETablas de Apache Iceberg™, aunque estén almacenadas fuera de Snowflake y gestionadas por un catálogo como AWS Glue o OneLake\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EVistas\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EVistas materializadas\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EFunciones definidas por el usuario (UDF) seguras\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003ESnowflake Native Apps\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EModelos de ML\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EVistas semánticas (vista previa privada)\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EDatos on‑premise, si están almacenados como archivos en un sistema de almacenamiento compatible con S3\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch3\u003EP: ¿Cómo puedo crear productos de datos basados en tablas de Iceberg y Delta Lake?\u003C/h3\u003E\n\u003Cp\u003ESi gestionas datos fuera de Snowflake, en Apache Iceberg, por ejemplo, puedes hacer que esa tabla de Iceberg sea visible en Snowflake e incluirla como parte de un producto de datos en el Internal Marketplace. Esto permite que ese mismo producto de datos sea interoperable con otros motores de cómputo que puedan acceder a los mismos datos. \u003C/p\u003E\n\u003Ch3\u003EP: “Chat with your data product” es una función actualmente en vista previa privada. ¿Qué es y cómo funciona?\u003C/h3\u003E\n\u003Cp\u003ESnowflake presenta una función innovadora que permite a los consumidores de datos usar lenguaje natural para interactuar con un producto de datos. Para ello, el propietario del producto de datos debe incluir una \u003Ca href=\"https://docs.snowflake.com/en/user-guide/views-semantic/overview\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Evista semántica\u003C/a\u003E en el producto, que describe el contenido y la estructura de los datos, como relaciones, métricas, dimensiones, y comentarios y sinónimos opcionales. \u003C/p\u003E\n\u003Cp\u003ELa vista semántica es utilizada a continuación por \u003Ca href=\"https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-analyst\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ECortex Analyst\u003C/a\u003E de Snowflake, una función totalmente gestionada y basada en large language models (LLM) que ayuda a responder preguntas de negocio a partir de tus datos estructurados en Snowflake. El consumidor de datos puede entonces consultar el producto de datos de formas muy potentes. Las consultas en lenguaje natural se convierten automáticamente a SQL y se ejecutan para generar respuestas. El SQL generado puede revisarse y modificarse si se desea. El consumidor de datos también puede hacer preguntas abiertas como “¿en qué puede ayudarme este producto de datos?” o “¿cuáles son las limitaciones de este producto de datos?”\u003C/p\u003E\n\u003Ch2\u003EWebinar sobre data mesh: cinco conclusiones \u003C/h2\u003E\n\u003Cp\u003EEstas son las cinco principales conclusiones e ideas clave de nuestro webinar sobre data mesh: \u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EEl data mesh tiene como objetivo abordar las limitaciones de la gestión de datos centralizada tradicional\u003C/b\u003E mediante la descentralización de la propiedad de los datos y la capacitación de los dominios de negocio para gestionar sus propios datos. La evaluación del data mesh requiere una reflexión cuidadosa para determinar si la implementación sociotécnica y las capacidades se alinean con los objetivos empresariales. \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003ESnowflake ofrece una plataforma que respalda los principios de data mesh\u003C/b\u003E al permitir una propiedad de datos escalable y gobernada, facilitar el uso compartido de productos de datos y reducir la complejidad y los costes.   \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EInternal Marketplace es una función clave de Snowflake\u003C/b\u003E que permite a los dominios publicar, descubrir, compartir y utilizar datos gobernados como productos de datos dentro de su empresa.   \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003ESnowflake otorga autonomía a los equipos de dominio\u003C/b\u003E al proporcionarles entornos independientes con sus propios recursos de almacenamiento y cómputo, y, a su vez, facilita la colaboración y el data sharing entre dominios.   \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003ESnowflake ayuda a reducir la complejidad y los costes\u003C/b\u003E de crear y operar una plataforma de productos de datos al ofrecer un servicio totalmente gestionado y preintegrado con una amplia gama de funciones.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003ESnowflake se integra con un amplio ecosistema de herramientas y servicios,\u003C/b\u003E lo que permite a las empresas crear arquitecturas personalizadas según sus necesidades.    \u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cp\u003EAl empoderar a los dominios de negocio, facilitar el data sharing y reducir la complejidad, una arquitectura de data mesh puede ayudar a las organizaciones a aprovechar todo el potencial de sus datos y obtener mejores resultados empresariales. Sin embargo, crear y operar un data mesh requiere una combinación de visión, alineación y capacidades técnicas. Necesitarás contar con una variedad de partes interesadas, herramientas y soluciones para tener éxito. La plataforma de Snowflake ofrece una base de soluciones potente y completa para las organizaciones que se encuentran en este camino hacia el data mesh.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text","image","blog_text_424278392","image_209205566","blog_text_1320022733"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"columnClassNames":{"premium_content_bann":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnCount":12,"appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{"premium_content_bann":{"id":"premium-content-banner-56d8ed5b52","contentHeadline":"Snowflake para data mesh","contentDescription":"Ofrece un control basado en dominios usando una infraestructura de autoservicio como 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Snowflake"},{"authorImage":{"id":"image-a4b648fef5","lazyEnabled":true,"alt":"Matthias Nicola","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--448628d1-4404-47d5-bf58-d8ee8c195da5/matthias-nicola.jpg?preferwebp=true&quality=85","height":"200","width":"200",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-851122a8e4","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/matthias-nicola/"},"linkTargetContentType":"DOCUMENT_LEARN","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Matthias Nicola"},"authorTitle":"Principal Data Platform Architect, Field CTO 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