{"id":1325,"date":"2018-09-25T13:07:37","date_gmt":"2018-09-25T13:07:37","guid":{"rendered":"https:\/\/lisdatasolutions.sidnpre.com\/2018\/09\/25\/5-aplicaciones-del-big-data-para-el-sector-textil\/"},"modified":"2022-08-01T15:39:34","modified_gmt":"2022-08-01T15:39:34","slug":"5-aplicaciones-del-big-data-para-el-sector-textil","status":"publish","type":"post","link":"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/","title":{"rendered":"5 aplicaciones del Big Data para el sector textil"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_55 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title \" >Tabla de contenidos<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\" role=\"button\"><label for=\"item-69f5650a98814\" ><span class=\"\"><span style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input aria-label=\"Toggle\" aria-label=\"item-69f5650a98814\"  type=\"checkbox\" id=\"item-69f5650a98814\"><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/#%C2%BFEn_que_puede_beneficiar_el_Big_Data_al_sector_textil\" title=\"\u00bfEn qu\u00e9 puede beneficiar el Big Data al sector textil?\">\u00bfEn qu\u00e9 puede beneficiar el Big Data al sector textil?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/#VER_PREDECIR_AVISAR_Prediccion_con_alarmas\" title=\"VER, PREDECIR, AVISAR (Predicci\u00f3n con alarmas)\">VER, PREDECIR, AVISAR (Predicci\u00f3n con alarmas)<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"%C2%BFEn_que_puede_beneficiar_el_Big_Data_al_sector_textil\"><\/span>\u00bfEn qu\u00e9 puede beneficiar el Big Data al sector textil?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>El <strong>Big Data<\/strong> nos permite identificar patrones ocultos en los datos, aplicando t\u00e9cnicas avanzadas de an\u00e1lisis de datos se pueden resolver preguntas de negocio del <strong>sector textil<\/strong> como:<\/p>\n<ul>\n<li>\u00bfC\u00f3mo se va a comportar determinada familia de producto? (bolsos, chaquetas, zapatos)<\/li>\n<li>\u00bfQu\u00e9 color de bolso se va a llevar la pr\u00f3xima temporada?<\/li>\n<li><strong>Predecir la demanda<\/strong>\u00a0en funci\u00f3n del comportamiento de los compradores<\/li>\n<li>Podr\u00e9 calcular mis stocks de maniobra y seguridad para satisfacer la demanda<\/li>\n<li>\u00bfC\u00f3mo va afectar la meteorolog\u00eda a mis ventas?<\/li>\n<\/ul>\n<p>Mucha de esta informaci\u00f3n ya se encuentra en nuestros sistemas, pero\u2026 adem\u00e1s\u2026! Gracias al <strong>Big Data para el sector textil,<\/strong> podremos vincular informaci\u00f3n aparentemente no relacionada como pueden ser bases de datos meteorol\u00f3gicas, redes sociales, bases de datos abiertas (open data)\u2026<\/p>\n<h2><span class=\"ez-toc-section\" id=\"VER_PREDECIR_AVISAR_Prediccion_con_alarmas\"><\/span><strong>VER, PREDECIR, AVISAR (Predicci\u00f3n con alarmas)<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Con las herramientas y las t\u00e9cnicas adecuadas, el Big Data nos permite:<\/p>\n<ul>\n<li>Ver lo que sucede en nuestra empresa, en nuestro entorno. Mucha informaci\u00f3n ya la tenemos, oculta entre una monta\u00f1a de datos. El Big Data nos permite hacerla visible.<\/li>\n<li>Predecir lo que puede pasar, integrando todas aquellas variables que de manera crucial nos influyen en las estimaciones de nuestros productos textiles.<\/li>\n<li>Avisar de anomal\u00edas y comportamientos extra\u00f1os. Monitorizar nuestras actuaciones y descubrir cuando nos estamos saliendo de los par\u00e1metros adecuados de forma preventiva.<\/li>\n<\/ul>\n<p>Todas estas preguntas y muchas m\u00e1s, se pueden contestar mediante an\u00e1lisis de datos con t\u00e9cnicas \u201c<strong>Big Data<\/strong>\u201d. El <strong>Big Data<\/strong> puede ayudar a resolver muchas preguntas de negocio del <strong>sector textil<\/strong>.<\/p>\n<p>Si quieres ver alg\u00fan ejemplo de <strong>proyectos de big data para el sector textil<\/strong>, no dudes en ponerte en contacto con nosotros\u00a0en <a href=\"mailto:info@lisdatasolutions.com\">info@lisdatasolutions.com<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u00bfEn qu\u00e9 puede beneficiar el Big Data al sector textil? El Big Data nos permite identificar patrones ocultos en los datos, aplicando t\u00e9cnicas avanzadas de an\u00e1lisis de datos se pueden resolver preguntas de negocio del sector textil como: \u00bfC\u00f3mo se va a comportar determinada familia de producto? (bolsos, chaquetas, zapatos) \u00bfQu\u00e9 color de bolso se [&hellip;]<\/p>\n","protected":false},"author":21,"featured_media":1326,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0},"categories":[111,26],"tags":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>5 aplicaciones del Big Data para el sector textil | LIS Data Solutions<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"5 aplicaciones del Big Data para el sector textil | LIS Data Solutions\" \/>\n<meta property=\"og:description\" content=\"\u00bfEn qu\u00e9 puede beneficiar el Big Data al sector textil? El Big Data nos permite identificar patrones ocultos en los datos, aplicando t\u00e9cnicas avanzadas de an\u00e1lisis de datos se pueden resolver preguntas de negocio del sector textil como: \u00bfC\u00f3mo se va a comportar determinada familia de producto? (bolsos, chaquetas, zapatos) \u00bfQu\u00e9 color de bolso se [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/\" \/>\n<meta property=\"og:site_name\" content=\"LIS Data Solutions\" \/>\n<meta property=\"article:published_time\" content=\"2018-09-25T13:07:37+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2022-08-01T15:39:34+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.lisdatasolutions.com\/wp-content\/uploads\/2022\/07\/textil-tendencias.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"600\" \/>\n\t<meta property=\"og:image:height\" content=\"288\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Natalia Andueza\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Escrito por\" \/>\n\t<meta name=\"twitter:data1\" content=\"Natalia Andueza\" \/>\n\t<meta name=\"twitter:label2\" content=\"Tiempo de lectura\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutos\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/\",\"url\":\"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/\",\"name\":\"5 aplicaciones del Big Data para el sector textil | LIS Data Solutions\",\"isPartOf\":{\"@id\":\"https:\/\/www.lisdatasolutions.com\/es\/#website\"},\"datePublished\":\"2018-09-25T13:07:37+00:00\",\"dateModified\":\"2022-08-01T15:39:34+00:00\",\"author\":{\"@id\":\"https:\/\/www.lisdatasolutions.com\/es\/#\/schema\/person\/b2748ac1971664b77f38389a77eb1fc7\"},\"breadcrumb\":{\"@id\":\"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/#breadcrumb\"},\"inLanguage\":\"es\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Portada\",\"item\":\"https:\/\/www.lisdatasolutions.com\/es\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"5 aplicaciones del Big Data para el sector textil\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.lisdatasolutions.com\/es\/#website\",\"url\":\"https:\/\/www.lisdatasolutions.com\/es\/\",\"name\":\"LIS Data Solutions\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.lisdatasolutions.com\/es\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"es\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.lisdatasolutions.com\/es\/#\/schema\/person\/b2748ac1971664b77f38389a77eb1fc7\",\"name\":\"Natalia Andueza\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"es\",\"@id\":\"https:\/\/www.lisdatasolutions.com\/es\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/67d34db2d9aca971aeec85ef05923c86?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/67d34db2d9aca971aeec85ef05923c86?s=96&d=mm&r=g\",\"caption\":\"Natalia Andueza\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"5 aplicaciones del Big Data para el sector textil | LIS Data Solutions","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/","og_locale":"es_ES","og_type":"article","og_title":"5 aplicaciones del Big Data para el sector textil | LIS Data Solutions","og_description":"\u00bfEn qu\u00e9 puede beneficiar el Big Data al sector textil? El Big Data nos permite identificar patrones ocultos en los datos, aplicando t\u00e9cnicas avanzadas de an\u00e1lisis de datos se pueden resolver preguntas de negocio del sector textil como: \u00bfC\u00f3mo se va a comportar determinada familia de producto? (bolsos, chaquetas, zapatos) \u00bfQu\u00e9 color de bolso se [&hellip;]","og_url":"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/","og_site_name":"LIS Data Solutions","article_published_time":"2018-09-25T13:07:37+00:00","article_modified_time":"2022-08-01T15:39:34+00:00","og_image":[{"width":600,"height":288,"url":"https:\/\/www.lisdatasolutions.com\/wp-content\/uploads\/2022\/07\/textil-tendencias.jpg","type":"image\/jpeg"}],"author":"Natalia Andueza","twitter_card":"summary_large_image","twitter_misc":{"Escrito por":"Natalia Andueza","Tiempo de lectura":"2 minutos"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/","url":"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/","name":"5 aplicaciones del Big Data para el sector textil | LIS Data Solutions","isPartOf":{"@id":"https:\/\/www.lisdatasolutions.com\/es\/#website"},"datePublished":"2018-09-25T13:07:37+00:00","dateModified":"2022-08-01T15:39:34+00:00","author":{"@id":"https:\/\/www.lisdatasolutions.com\/es\/#\/schema\/person\/b2748ac1971664b77f38389a77eb1fc7"},"breadcrumb":{"@id":"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/#breadcrumb"},"inLanguage":"es","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/www.lisdatasolutions.com\/es\/blog\/5-aplicaciones-del-big-data-para-el-sector-textil\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Portada","item":"https:\/\/www.lisdatasolutions.com\/es\/"},{"@type":"ListItem","position":2,"name":"5 aplicaciones del Big Data para el sector textil"}]},{"@type":"WebSite","@id":"https:\/\/www.lisdatasolutions.com\/es\/#website","url":"https:\/\/www.lisdatasolutions.com\/es\/","name":"LIS Data Solutions","description":"","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.lisdatasolutions.com\/es\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"es"},{"@type":"Person","@id":"https:\/\/www.lisdatasolutions.com\/es\/#\/schema\/person\/b2748ac1971664b77f38389a77eb1fc7","name":"Natalia Andueza","image":{"@type":"ImageObject","inLanguage":"es","@id":"https:\/\/www.lisdatasolutions.com\/es\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/67d34db2d9aca971aeec85ef05923c86?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/67d34db2d9aca971aeec85ef05923c86?s=96&d=mm&r=g","caption":"Natalia Andueza"}}]}},"_links":{"self":[{"href":"https:\/\/www.lisdatasolutions.com\/es\/wp-json\/wp\/v2\/posts\/1325"}],"collection":[{"href":"https:\/\/www.lisdatasolutions.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.lisdatasolutions.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.lisdatasolutions.com\/es\/wp-json\/wp\/v2\/users\/21"}],"replies":[{"embeddable":true,"href":"https:\/\/www.lisdatasolutions.com\/es\/wp-json\/wp\/v2\/comments?post=1325"}],"version-history":[{"count":1,"href":"https:\/\/www.lisdatasolutions.com\/es\/wp-json\/wp\/v2\/posts\/1325\/revisions"}],"predecessor-version":[{"id":3679,"href":"https:\/\/www.lisdatasolutions.com\/es\/wp-json\/wp\/v2\/posts\/1325\/revisions\/3679"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.lisdatasolutions.com\/es\/wp-json\/wp\/v2\/media\/1326"}],"wp:attachment":[{"href":"https:\/\/www.lisdatasolutions.com\/es\/wp-json\/wp\/v2\/media?parent=1325"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.lisdatasolutions.com\/es\/wp-json\/wp\/v2\/categories?post=1325"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.lisdatasolutions.com\/es\/wp-json\/wp\/v2\/tags?post=1325"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}