Si bien los enfoques tradicionales de usar data lakes y almacenes de datos pueden ser eficaces, tienen deficiencias, en particular en entornos empresariales grandes. En este curso, se presenta el concepto del data lakehouse y los productos de Google Cloud que se usan para crear uno. Una arquitectura de lakehouse usa fuentes de datos de estándares abiertos y combina las mejores funciones de los data lakes y los almacenes de datos, lo que aborda muchas de sus deficiencias.
Modernizing Data Lakes and Data Warehouses with GCP en Español
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Modernizing Data Lakes and Data Warehouses with GCP en Español
This course is part of multiple programs.
Instructor: Google Cloud Training
1,739 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
4.8
(96 reviews)
Intermediate level
Some related experience required
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Diferencia entre un data lake, un almacén de datos y un data lakehouse
Explica el concepto de data lakehouse y cómo aborda las limitaciones de los data lakes y almacenes de datos tradicionales
Identifica varias fuentes de datos que BigQuery puede consultar
Reconoce las capacidades de usar BigQuery para crear modelos de IA y acceder a ellos
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
4 assignments
Taught in Spanish
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There are 7 modules in this course
Presenta al estudiante los temas que se abordarán en el curso y las habilidades que aprenderá.
What's included
1 plugin
En este módulo, se presentan los conceptos fundamentales de los data lakes y los almacenes de datos, lo que sienta las bases para las arquitecturas modernas en Google Cloud.
What's included
1 assignment4 plugins
En este módulo, se detalla el concepto de un lakehouse y se presentan los productos de Google Cloud que se usan con más frecuencia para crear un data lakehouse moderno con formatos de código abierto.
What's included
1 assignment1 app item7 plugins
En este módulo, se explora BigQuery como la piedra angular de un almacén de datos moderno y se presenta BigLake para unificar el acceso en el data lake y el almacén de datos.
What's included
1 assignment1 app item4 plugins
Este módulo se enfoca en patrones arquitectónicos avanzados para el lakehouse, incluidos el procesamiento de datos, la organización y la administración integral de datos en BigQuery, Cloud Storage y BigLake.
What's included
1 assignment5 plugins
En este módulo, se proporcionan labs para profundizar las habilidades en las herramientas y tecnologías que usa un lakehouse en Google Cloud. Además, se brinda una descripción general de las prácticas recomendadas, los errores comunes y las tendencias futuras.
What's included
2 app items2 plugins
Resumir las capacidades arquitectónicas y operativas del data lakehouse centrado en BigQuery, que abarca la administración, el análisis avanzado y el aprendizaje automático
What's included
1 plugin
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Instructor
Instructor ratings
4.7 (23 ratings)Offered by
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Showing 3 of 96
CG
5
Reviewed on Sep 8, 2020
love the last section where we could put on practice the knowledge obtained
CL
5
Reviewed on Aug 24, 2022
Excelentes definiciones y explicaciones en términos generales.
C
4
Reviewed on Sep 23, 2021
Gran curso para orientar las posibles soluciones que ofrece GCP en torno a los Data Lakes y Data Warehouses
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
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