{"id":31421,"date":"2025-07-16T20:09:00","date_gmt":"2025-07-17T02:09:00","guid":{"rendered":"https:\/\/reseller.lat\/?p=31421"},"modified":"2025-07-16T23:14:57","modified_gmt":"2025-07-17T05:14:57","slug":"ia-es-hora-de-poner-orden-en-los-datos-pure-storage","status":"publish","type":"post","link":"https:\/\/reseller.lat\/?p=31421","title":{"rendered":"IA, es hora de poner orden en los datos: Pure Storage"},"content":{"rendered":"\n

La IA ha pasado<\/strong> de ser una curiosidad a una prioridad<\/strong> empresarial. En Am\u00e9rica Latina, el debate<\/strong> est\u00e1 cambiando. Los l\u00edderes<\/strong> empresariales<\/strong> ya no se preguntan: “\u00bfPodemos implementar IA?” sino “\u00bfEst\u00e1 dando resultados?”.<\/p>\n\n\n\n

La novedad<\/strong>\u00a0se desvanece y las\u00a0expectativas<\/strong>\u00a0se intensifican. \u00bfCu\u00e1l es el\u00a0retorno<\/strong>? \u00bfQu\u00e9\u00a0valor<\/strong>\u00a0estamos descubriendo? \u00bfQu\u00e9 problemas estamos resolviendo<\/strong>\u00a0realmente?<\/p>\n\n\n\n

Pero hay un punto ciego<\/strong> en muchas de estas conversaciones. Las empresas se apresuran a adoptar herramientas<\/strong> de IA y a aumentar su capacidad de procesamiento.<\/p>\n\n\n\n

Pocas dedican el tiempo suficiente<\/strong> a solucionar lo que realmente importa: los datos<\/strong> que alimentan esos sistemas<\/strong>.<\/p>\n\n\n\n

La realidad es la siguiente: datos desordenados<\/strong> significa IA desordenada. Si tu organizaci\u00f3n tiene cinco versiones<\/strong> del mismo conjunto de datos circulando, almacenadas en diferentes departamentos<\/strong>.<\/p>\n\n\n\n

Y nadie est\u00e1 seguro de cu\u00e1l es la m\u00e1s precisa<\/strong> o actualizada, no obtendr\u00e1s inteligencia, sino ruido<\/strong>.<\/p>\n\n\n\n

Y en sectores como\u00a0finanzas<\/strong>, salud o\u00a0administraci\u00f3n p\u00fablica<\/strong>, ese ruido puede llevar a decisiones\u00a0arriesgadas<\/strong>. Invertir\u00a0m\u00e1s recursos<\/strong>\u00a0computacionales en el problema no servir\u00e1 de nada; s\u00f3lo te llevar\u00e1 a la\u00a0respuesta equivocada<\/strong>\u00a0m\u00e1s r\u00e1pido.<\/p>\n\n\n\n

Para que la\u00a0IA funcione correctamente, necesitamos hacer el\u00a0trabajo duro\u00a0y poco atractivo:<\/strong><\/h2>\n\n\n\n

Depurar<\/strong> los datos, estandarizarlos y asegurarnos<\/strong> de que todos trabajen con la misma versi\u00f3n<\/strong> de la verdad. Esto implica romper con los silos<\/strong>, establecer reglas claras sobre c\u00f3mo se gestionan<\/strong> los datos e invertir en los sistemas adecuados para rastrearlos<\/strong> y gestionarlos.<\/p>\n\n\n\n

No se trata de una tarea puntual<\/strong>, sino de un cambio<\/strong> de mentalidad. Pi\u00e9nsalo como un volante: unos datos limpios<\/strong> conducen a mejores modelos, que ayudan a tomar decisiones<\/strong> m\u00e1s inteligentes.<\/p>\n\n\n\n

Y esas decisiones generan datos<\/strong> a\u00fan m\u00e1s \u00fatiles. Pero el volante s\u00f3lo gira si la informaci\u00f3n es s\u00f3lida<\/strong>.<\/p>\n\n\n\n

Tambi\u00e9n debemos tomarnos en serio<\/strong> la responsabilidad de los datos. Esto significa saber de d\u00f3nde provienen<\/strong>, c\u00f3mo se han modificado y qui\u00e9n tiene acceso<\/strong> a ellos. Sin esa transparencia<\/strong>, no podemos construir sistemas en los que confiemos<\/strong>, ni tampoco los reguladores, los clientes<\/strong> ni el p\u00fablico.<\/p>\n\n\n\n

En el D\u00eda de Apreciaci\u00f3n de la Inteligencia Artificial<\/strong>, centremos la atenci\u00f3n en los cimientos<\/strong>.<\/p>\n\n\n\n

Porque el\u00a0verdadero progreso<\/strong>\u00a0no proviene de adoptar la herramienta m\u00e1s reciente, sino de\u00a0construir la infraestructura<\/strong>, la mentalidad y la cultura adecuadas<\/strong>\u00a0para respaldarla.<\/p>\n\n\n\n

Por Douglas Wallace<\/a>, gerente de Ventas Distrital, Am\u00e9rica Latina y el Caribe (Excepto Brasil) en Pure Storage<\/a>.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

La IA ha pasado de ser una curiosidad a una prioridad empresarial. En Am\u00e9rica Latina, el debate est\u00e1 cambiando. Los l\u00edderes empresariales ya no se preguntan: “\u00bfPodemos implementar IA?” sino “\u00bfEst\u00e1 dando resultados?”. La novedad\u00a0se desvanece y las\u00a0expectativas\u00a0se intensifican. \u00bfCu\u00e1l es el\u00a0retorno? \u00bfQu\u00e9\u00a0valor\u00a0estamos descubriendo? \u00bfQu\u00e9 problemas estamos resolviendo\u00a0realmente? Pero hay un punto ciego en muchas de estas conversaciones. Las empresas se apresuran a adoptar herramientas de IA y […]<\/p>\n","protected":false},"author":3,"featured_media":31424,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[51,84,61],"tags":[1951,350,1948,1947,1949,1920,180,182,111,1950,1946,1048,1952],"class_list":["post-31421","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-latam","category-opinion","category-todas-las-noticias","tag-adopcion","tag-datos","tag-depurar","tag-douglas-wallace","tag-estandarizar","tag-herramientas","tag-ia","tag-infraestructura","tag-inteligencia-artificial","tag-lideres","tag-orden","tag-pure-storage","tag-silos"],"yoast_head":"\nIA, es hora de poner orden en los datos: Pure Storage<\/title>\n<meta name=\"description\" content=\"Para que la IA funcione correctamente, hay que depurar los datos, estandarizarlos y asegurarnos de que todos trabajen con la misma versi\u00f3n.\" 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