Coursera

Arquitecturas de Big Data (Coursera)

Offered by Universidad de los Andes,

El curso de Arquitecturas de Big Data busca que identifiques las características de una solución de Big Data, los datos asociados a estas soluciones, la infraestructura requerida, y las técnicas de procesamiento escalable. Desarrollaremos ejemplos usando infraestructuras basadas en Hadoop y en Spark, teniendo presente la pertinencia de las plataformas basadas en nube pública para soportar la escalabilidad de estas soluciones.

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El curso está dirigido a personas con conocimientos básicos en manejo de herramientas computacionales y programación en al menos uno de estos lenguajes (Python, Java).
Dado que en este curso se hará uso de un programa descargable, aseguraté de tener un computador con la siguiente configuración mínima:
Mínimo 8 GB de memoria RAM.
Mínimo 200 GB de espacio libre en disco.
Alguno de los siguientes sistemas operativos: Windows, Linux, Macintosh, o Solaris.
Course 1 of 3 in the Plataformas para procesar datos no tradicionales Specialization.
What You Will Learn

Determinar la pertinencia de usar tecnologías de Big Data a un problema dado
Desarrollar proyectos sencillos de procesamiento escalable en Spark.   
Conocer el rol de la computación en la nube como alternativa para procesar y almacenar Big Data, así como sus ventajas y riesgos
Identificar las características de una solución de Big Data, la infraestructura requerida, y las técnicas de procesamiento escalable.

Syllabus

WEEK 1
Introducción
Te damos la bienvenida al curso "Arquitecturas de Big Data". Te invitamos a realizar las lecturas sobre acceso al curso y recursos.
¿Qué es Big Data?
Bienvenido al primer módulo del curso. En este módulo responderemos a la pregunta ¿Qué es el Big Data? Para ellos nos centraremos en conocer como llegamos hoy al Big Data, cuáles son las 3V principales e identificaremos las diferencias que tiene Big Data con las arquitecturas tradicionales.

WEEK 2
¿Cómo almacenamos Big Data?
Bienvenido al segundo módulo del curso. Dentro de este módulo nos centraremos en responder a la pregunta ¿Cómo almacenamos Big Data? Para ello identificaremos los requerimientos y desafíos de almacenamiento de Big Data, conoceremos acerca de la arquitectura conceptual y veremos algunos ejemplos, y conoceremos sobre sistemas de archivos distribuidos y sistemas manejadores de bases de datos NoSQL.

WEEK 3
¿Cómo procesamos Big Data?
Bienvenido al tercer módulo del curso. Durante el desarrollo de este módulo nos enfocaremos en responder a la pregunta ¿Cómo procesamos Big Data? Para ello trabajaremos en tres temas principales: Procesamiento escalable y Map-Rediuce, Spark y Arquitecturas para procesamientos de datos de flujos.

WEEK 4
¿Cuál es el rol de la nube en entornos Big Data?
Te damos la bienvenida al cuarto y último módulo de nuestro curso. Durante este módulo responderemos a la pregunta ¿Cuál es el rol de la nube en entornos Big Data? Para ello, una vez comprendamos los aspectos conceptuales, revisaremos las posibilidades de procesamiento y almacenamiento que hacen de la nube un entorno ideal para Big Data. También revisaremos las ventajas y riesgos de utilizar servicios públicos en la nube.

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