Generative AI: use cases
Generative AI in the enterprise is no longer an experiment: applied to concrete processes, it reduces costs, speeds up tasks and improves the experience of customers and employees. The key to ROI…
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The 10 most common CV mistakes: How to face them
CV mistakes 2026: What AI-powered ATS reject and how to fix it In September 2020 we published the ten most common mistakes in a CV. Five years later, the landscape has changed…
Blockchain in the enterprise: beyond cryptocurrencies
Beyond crypto: traceability, smart contracts and digital identity. Where the blockchain adds value to the enterprise.
Languages, Frameworks, SDKs — churras and merinas in Swift
Swift 6.0 (Sept 2024): structured concurrency (compile-time data-race safety), stable macros, ownership manifesto implemented. The only mainstream language with memory safety + concurrency without GC + high ergonomics. Server-side: Vapor 4, Hummingbird…
Talent acquisition 2026: the end of “post and pray” and the rise of autonomous AI agents
Talent acquisition 2026: the end of “post and pray” and the rise of autonomous AI agents In 2019 we talked about “AI and automation” as a trend. In 2026, generative AI has…
ELT or ETL, Which Is Better?
SQLMesh — Replaces dbt in serious projects: understands column-level dependencies, plans diffs, isolated virtual environments, native CI. 40% reduction in model deployment time vs pure dbt. Apache Iceberg (Polaris/Unity Catalog) — The…
Alternative Data 2026: AI Agents, RAG and Intelligent Web Scraping
Alternative Data 2026: AI Agents, RAG and Intelligent Web Scraping In 2019 we published the original version of this article. Back then, the “information advantage” in hedge funds came from buying satellite…
Alternative Data 2026: AI Agents, RAG and Intelligent Web Scraping
Alternative Data 2026: AI Agents, RAG and Intelligent Web Scraping In 2019 we published the original version of this article. Back then, the “information advantage” in hedge funds came from buying satellite…
Business Intelligence vs. Data Analytics: diferencias claras
Diferencias entre Business Intelligence y Data Analytics, cuándo usar cada uno y cómo se complementan para tomar mejores decisiones.
Business Intelligence vs. Data Analytics: the key differences
In the debate of Business Intelligence vs Data Analytics, the main difference lies in the time focus and the objective: Business Intelligence (BI) answers “what has happened and what is happening?” through…