// Lightweight i18n: a dictionary + a hook + a language toggle. const I18N = { es: { // nav "nav.work": "Logros", "nav.stack": "Stack", "nav.edu": "Educación", "nav.contact": "Contacto", "nav.hire": "Contáctame", "nav.badge": "portfolio · 2026", "nav.cv": "CV", // cv section "cv.label": "Currículum · versión 2026", "cv.title.a": "Descarga el CV", "cv.title.em": "en un solo archivo.", "cv.kicker": "Toda la experiencia, el stack y los logros verificados en un PDF limpio, listo para compartir con tu equipo.", "cv.filename": "Ana-Garcia-CV.pdf", "cv.meta.pages": "páginas", "cv.meta.lang": "idioma", "cv.meta.langValue": "Español", "cv.meta.updated": "actualizado", "cv.meta.updatedValue": "abr 2026", "cv.meta.size": "tamaño", "cv.download": "Descargar PDF", "cv.preview": "Vista previa", "cv.previewNote": "Abre en una pestaña nueva", // hero "hero.availability": "Disponible — proyectos Q2/Q3 2026", "hero.soy": "soy ", "hero.summary": "Transformo datos en decisiones estratégicas. Más de 3 años diseñando dashboards, automatizando reportes y construyendo procesos ETL que le ahorran tiempo —y errores— a equipos que operan a escala.", "hero.cta.work": "Ver logros", "hero.cta.mail": "Escribirme", "hero.meta.location": "Ubicación", "hero.meta.experience": "Experiencia", "hero.meta.focus": "Enfoque", "hero.meta.focus.v": "BI · ETL · Automatización", "hero.meta.years": "3+ años", "hero.scroll": "scroll · logros", // hero roles "role.analyst": "Data Analyst", "role.bi": "Especialista en BI", "role.auto": "Experta en Automatización", // hero visual "visual.file": "dashboards / overview.pbix", "visual.sla": "Reacción SLA", "visual.slaNote": "vs. baseline Q1", "visual.claims": "Reclamos", "visual.claimsNote": "dataset mensual", "visual.savings": "Ahorro", "visual.savingsUnit": "/ sem", "visual.savingsNote": "automatización", "visual.errors": "Tiempo de reacción (h) · mensual", "visual.errorsDelta": "−35% post rollout", "visual.live": "v2025.04 · live", // bento / work "work.label": "Logros · experiencia en retail", "work.title.a": "Datos operando a escala,", "work.title.b": "con impacto medible.", "work.kicker": "Selección de resultados de alto volumen durante +3 años como analista en retail: reclamos, SLA, automatización y gobernanza.", "work.footnote": "Contexto · analista en grandes volúmenes de datos de retail", "work.verified": "métricas verificadas internamente", "work.period": "periodo 2022 – 2025", // tiles "tile.chip.case": "Caso destacado · retail", "tile.chip.auto": "Automatización", "tile.chip.etl": "ETL", "tile.chip.reporting": "Reporting", "tile.etl.pipeline": "pipeline · daily", // highlights (per id) "hl.reclamos.title": "Dashboard operativo · +25.000 reclamos", "hl.reclamos.body": "Diseño y construcción de un dashboard consolidado que unifica +25.000 reclamos mensuales desde múltiples fuentes. Redujo el tiempo de reacción operativa en un 35% al exponer SLA, backlog y causas-raíz en una sola vista.", "hl.reclamos.kpiLabel": "tiempo de reacción", "hl.automatizacion.title": "Automatización SQL + Excel", "hl.automatizacion.body": "Scripts de consolidación y macros que reemplazaron tareas manuales recurrentes. 12 horas semanales liberadas para análisis en lugar de data-wrangling.", "hl.automatizacion.kpiLabel": "ahorradas / semana", "hl.etl.title": "Procesos ETL · SQL Server · Backstore · Jarvis", "hl.etl.body": "Pipelines de extracción y normalización entre SQL Server, Backstore y Jarvis. Datos conciliados a diario, trazables y listos para consumo analítico.", "hl.standardization.title": "Estandarización de reporting", "hl.standardization.body": "Plantillas, métricas y naming unificados entre áreas. −20% errores en reportes publicados.", "hl.standardization.kpiLabel": "errores de reporting", // stack "stack.label": "Tech stack · herramientas en producción", "stack.title.a": "Herramientas con las que", "stack.title.em": "entrego resultados", "stack.title.b": "a diario.", "stack.kicker": "Agrupadas por lenguaje, visualización y metodología. Los niveles reflejan proyectos reales en los últimos 36 meses.", "stack.skillsSuffix": "skills", "stack.group.lang": "Lenguajes", "stack.group.viz": "Visualización", "stack.group.tools": "Herramientas & Métodos", // timeline / edu "edu.label": "Formación académica · continua", "edu.title.a": "Una base técnica", "edu.title.em": "actualizada cada año.", "edu.kicker": "De técnico a ingeniera, con especialización en Business Intelligence y Power BI. Aprendizaje constante.", "edu.kind.course": "course", "edu.kind.diploma": "diploma", "edu.kind.degree": "degree", "edu.kind.technician": "technician", "edu.powerbi.title": "Power BI 2025", "edu.powerbi.org": "Curso especializado", "edu.powerbi.detail": "DAX avanzado, modelado tabular, rendimiento.", "edu.diplomado.title": "Diplomado en Inteligencia de Negocios", "edu.diplomado.org": "Universidad / Postgrado", "edu.diplomado.detail": "Gobierno de datos, arquitectura BI, visualización.", "edu.ingenieria.title": "Ingeniería en Informática", "edu.ingenieria.org": "Universidad", "edu.ingenieria.detail": "Titulada con mención en sistemas de información.", "edu.tecnico.title": "Técnico en Informática", "edu.tecnico.org": "Instituto", "edu.tecnico.detail": "Base técnica en desarrollo y bases de datos.", // footer "contact.label": "Contacto · disponible para proyectos", "contact.title.a": "Hablemos de", "contact.title.em": "tus datos.", "contact.kicker": "Consultoría BI, dashboards, automatización y pipelines ETL. Remoto desde Santiago o presencial en Las Condes.", "contact.email": "Email", "contact.phone": "Teléfono", "contact.location": "Ubicación", "contact.locationValue": "Las Condes, Santiago", "footer.signA": "Data", "footer.signB": "Decisión", "footer.copy": "Santiago, CL", "footer.snapshot": "v2026.04 · snapshot", "footer.available": "disponible", }, en: { // nav "nav.work": "Work", "nav.stack": "Stack", "nav.edu": "Education", "nav.contact": "Contact", "nav.hire": "Contact me", "nav.badge": "portfolio · 2026", "nav.cv": "CV", // cv section "cv.label": "Resume · 2026 edition", "cv.title.a": "Download the CV", "cv.title.em": "in a single file.", "cv.kicker": "All the experience, stack, and verified achievements in a clean PDF — ready to share with your team.", "cv.filename": "Ana-Garcia-CV.pdf", "cv.meta.pages": "pages", "cv.meta.lang": "language", "cv.meta.langValue": "Spanish", "cv.meta.updated": "updated", "cv.meta.updatedValue": "Apr 2026", "cv.meta.size": "size", "cv.download": "Download PDF", "cv.preview": "Preview", "cv.previewNote": "Opens in a new tab", // hero "hero.availability": "Available — Q2/Q3 2026 projects", "hero.soy": "I’m a ", "hero.summary": "I turn data into strategic decisions. 3+ years designing dashboards, automating reports, and building ETL processes that save time — and prevent mistakes — for teams operating at scale.", "hero.cta.work": "See work", "hero.cta.mail": "Get in touch", "hero.meta.location": "Location", "hero.meta.experience": "Experience", "hero.meta.focus": "Focus", "hero.meta.focus.v": "BI · ETL · Automation", "hero.meta.years": "3+ years", "hero.scroll": "scroll · work", "role.analyst": "Data Analyst", "role.bi": "BI Specialist", "role.auto": "Automation Expert", "visual.file": "dashboards / overview.pbix", "visual.sla": "SLA reaction", "visual.slaNote": "vs. Q1 baseline", "visual.claims": "Claims", "visual.claimsNote": "monthly dataset", "visual.savings": "Savings", "visual.savingsUnit": "/ wk", "visual.savingsNote": "automation", "visual.errors": "Reaction time (h) · monthly", "visual.errorsDelta": "−35% post-rollout", "visual.live": "v2025.04 · live", "work.label": "Work · retail experience", "work.title.a": "Data operating at scale,", "work.title.b": "with measurable impact.", "work.kicker": "A selection of high-volume outcomes during 3+ years as a retail analyst: claims, SLA, automation, and governance.", "work.footnote": "Context · analyst on large retail datasets", "work.verified": "metrics internally verified", "work.period": "period 2022 – 2025", "tile.chip.case": "Featured case · retail", "tile.chip.auto": "Automation", "tile.chip.etl": "ETL", "tile.chip.reporting": "Reporting", "tile.etl.pipeline": "pipeline · daily", "hl.reclamos.title": "Operations dashboard · 25,000+ claims", "hl.reclamos.body": "Design and build of a consolidated dashboard that unifies 25,000+ monthly claims across multiple sources. Cut operational reaction time by 35% by exposing SLA, backlog, and root causes in a single view.", "hl.reclamos.kpiLabel": "reaction time", "hl.automatizacion.title": "SQL + Excel automation", "hl.automatizacion.body": "Consolidation scripts and macros that replaced recurring manual tasks. 12 weekly hours freed up for analysis instead of data-wrangling.", "hl.automatizacion.kpiLabel": "saved / week", "hl.etl.title": "ETL processes · SQL Server · Backstore · Jarvis", "hl.etl.body": "Extraction and normalization pipelines across SQL Server, Backstore, and Jarvis. Data reconciled daily, traceable, and ready for analytical consumption.", "hl.standardization.title": "Reporting standardization", "hl.standardization.body": "Unified templates, metrics, and naming across teams. −20% errors in published reports.", "hl.standardization.kpiLabel": "reporting errors", "stack.label": "Tech stack · tools in production", "stack.title.a": "Tools I use to", "stack.title.em": "deliver results", "stack.title.b": "every day.", "stack.kicker": "Grouped by language, visualization, and methodology. Levels reflect real projects over the last 36 months.", "stack.skillsSuffix": "skills", "stack.group.lang": "Languages", "stack.group.viz": "Visualization", "stack.group.tools": "Tools & Methods", "edu.label": "Education · always learning", "edu.title.a": "A technical foundation", "edu.title.em": "refreshed every year.", "edu.kicker": "From technician to engineer, specialized in Business Intelligence and Power BI. Continuous learning.", "edu.kind.course": "course", "edu.kind.diploma": "diploma", "edu.kind.degree": "degree", "edu.kind.technician": "technician", "edu.powerbi.title": "Power BI 2025", "edu.powerbi.org": "Specialized course", "edu.powerbi.detail": "Advanced DAX, tabular modeling, performance.", "edu.diplomado.title": "Business Intelligence Diploma", "edu.diplomado.org": "University / Postgraduate", "edu.diplomado.detail": "Data governance, BI architecture, visualization.", "edu.ingenieria.title": "Computer Engineering", "edu.ingenieria.org": "University", "edu.ingenieria.detail": "Graduate with a major in information systems.", "edu.tecnico.title": "Computer Technician", "edu.tecnico.org": "Institute", "edu.tecnico.detail": "Technical foundation in development and databases.", "contact.label": "Contact · available for projects", "contact.title.a": "Let’s talk about", "contact.title.em": "your data.", "contact.kicker": "BI consulting, dashboards, automation, and ETL pipelines. Remote from Santiago or on-site in Las Condes.", "contact.email": "Email", "contact.phone": "Phone", "contact.location": "Location", "contact.locationValue": "Las Condes, Santiago", "footer.signA": "Data", "footer.signB": "Decision", "footer.copy": "Santiago, CL", "footer.snapshot": "v2026.04 · snapshot", "footer.available": "available", }, }; const LangContext = React.createContext({ lang: "es", setLang: () => {} }); function LangProvider({ children }) { const [lang, setLangState] = React.useState(() => { try { return localStorage.getItem("ag.lang") || "es"; } catch { return "es"; } }); const setLang = React.useCallback((l) => { setLangState(l); try { localStorage.setItem("ag.lang", l); } catch {} document.documentElement.lang = l; }, []); React.useEffect(() => { document.documentElement.lang = lang; }, [lang]); const value = React.useMemo(() => ({ lang, setLang }), [lang, setLang]); return {children}; } function useT() { const { lang } = React.useContext(LangContext); const dict = I18N[lang] || I18N.es; const t = React.useCallback((key) => (dict[key] !== undefined ? dict[key] : key), [dict]); return { t, lang }; } function useLang() { return React.useContext(LangContext); } function LangToggle() { const { lang, setLang } = useLang(); const next = lang === "es" ? 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