Manuel Hernández Giuliani

  Original Post in LinkedIn Enterprise Data and AI leadership in 2026 and beyond is defined by the ability to translate business intent into scalable, governed, and AI-ready data platforms. It is no longer about managing technologies, but about orchestrating data, architecture, and decision systems as a unified capability. Leaders must balance innovation with control, embedding governance, metadata, and quality into every layer while enabling real-time, autonomous intelligence through AI and agents. The focus shifts from delivering data to delivering outcomes, where platforms become products, teams operate with ownership, and every data asset is designed to drive measurable business value.

  Original Post in LinkedIn I remember when I started working in IT back in 1995 reporting meant green-bar paper coming out of big machines, and big noise, in cold data centers. If you wanted a new report, it could take weeks. Sometimes months. Then came Data Warehousing; we structured everything. ETL before loading. Star schemas (thanks Ralph Kimball and your Bus Matrix). Governance and Methodology first. It was powerful, clean, reliable, controlled. But rigid. Then the world exploded with data; we enter to the age of Data Lakes (Big Data here and there). We moved from ETL to ELT. From structured-only to everything: logs, sensors, clicks, documents, images, videos. It felt like freedom. But without governance, many lakes became swamps. The next natural step was inevitable: Data Lakehouse. We wanted scale and control. Flexibility and trust. Governance embedded into the platform. One foundation for BI, Data Science, and now AI. And today, we are living another evolution emerging. No...

  Original Post in LinkedIn Really valuable initiative. AI conversations must move beyond hype and into execution, scale, governance, architecture, and domain expertise. Sustainable AI is not about models alone. It is about integrating AI into real enterprise data platforms and operational systems. Looking forward to listening to these episodes, especially the intersection between AI and industrial transformation. AI at scale requires engineering discipline. hashtag # AI hashtag # DataArchitecture hashtag # EnterpriseAI https://lnkd.in/egTAgNrR

  Original Post in LinkedIn Hello all, I have been reflecting a lot while preparing the next semester. AI skills are rising fast among students. But deep hands-on data engineering skills are decreasing. And that worries me. So I decided to change the way I teach Big Data. This year I will teach: • One program in English (39 students) • One program in Spanish (17 students) Same approach but evolving the structure significantly. As I mentioned before there is a clear trend: Students are becoming increasingly AI-proficient… but less hands-on in core data engineering and platform fundamentals. So I redesigned the course. The structure now includes: • 18 hours of theory • 14 hours of guided hands-on lab • 8 hours of stand-ups (individual Big Data topics + group final use case presentation) But the real shift is deeper. The lab is no longer tool-driven. It is architecture-driven. Students will learn by doing: – Agile SAFe methodology – GitHub & GitHub Organizations – Terraform (Infr...

Original Post in LinkedIn I'm heading to hashtag # 4YFN26 - where startups spark, corporates collaborate, and ideas take flight. Can’t wait to connect with visionary founders, game-changing solutions, and fellow VCs driving the next wave of innovation. Let’s make sparks happen! Register for your pass >> https://lnkd.in/e2fgHwmi

 Esta es una formación en PHP dedicado a las personas interesadas en aprender a programar en PHP desde cero. PHP es un lenguaje de programación de uso general que se adapta especialmente al desarrollo web. PHP puede ser desplegado en la mayoría de los servidores web y en todos los sistemas operativos y plataformas sin costo alguno. El lenguaje PHP se encuentra instalado en más de 20 millones de sitios web y en un millón de servidores. Capítulo 0 Capítulo 1

Hoy vamos a escuchar La catedral y El Bazar, un ensayo sobre el software de código abierto, escrito por el hacktivista Eric Raymond en 1997. El ensayo analiza dos modelos de producción de software bien diferenciados. Por un lado, la catedral, que representa el modelo de desarrollo más hermético y vertical característico del Software propietario; y por el otro el bazar, con su dinámica horizontal y "bulliciosa", que caracterizó al desarrollo del kernel Linux y otros proyectos de software libre que se potenciaron con el trabajo comunitario a través de Internet del código abierto. La Catedral y El Bazar - Completo La Catedral y El Bazar - Resumen La Catedral y El Bazar - Parte 1 La Catedral y El Bazar - Parte 2 La Catedral y El Bazar - Parte 3 La Catedral y El Bazar - Parte 4 La Catedral y El Bazar - Parte 5 La Catedral y El Bazar - Parte 6 La Catedral y El Bazar - Parte 7 La Catedral y El Bazar - Parte 8