Os pipelines de dados geralmente se encaixam em um desses três paradigmas: extração e carregamento (EL), extração, carregamento e transformação (ELT) ou extração, transformação e carregamento (ETL). Este curso descreve qual paradigma deve ser usado em determinadas situações e quando isso ocorre com dados em lote. Além disso, vamos falar sobre várias tecnologias no Google Cloud para transformação de dados, incluindo o BigQuery, a execução do Spark no Dataproc, gráficos de pipeline no Cloud Data Fusion e processamento de dados sem servidor com o Dataflow. Os participantes vão ganhar experiência prática na criação de componentes de pipelines de dados no Google Cloud usando o Qwiklabs.
Building Batch Data Pipelines on GCP em Português Brasileiro
Building Batch Data Pipelines on GCP em Português Brasileiro
This course is part of Data Engineer, Big Data and ML on Google Cloud em Português Specialization
Instructor: Google Cloud Training
Sponsored by Coursera Learning Team
Gain insight into a topic and learn the fundamentals.
4.7
(15 reviews)
Intermediate level
Some related experience required
17 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Analisar diferentes métodos de carregamento de dados: EL, ELT e ETL e quando usar cada um deles.
Executar o Hadoop no Dataproc, usar o Cloud Storage e otimizar os jobs do Dataproc.
Usar o Dataflow para criar pipelines de processamento de dados.
Gerenciar pipelines de dados com o Data Fusion e o Cloud Composer.
Details to know
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Assessments
4 assignments
Taught in Portuguese (Brazil)
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This course is part of the Data Engineer, Big Data and ML on Google Cloud em Português Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 6 modules in this course
Neste módulo, vamos apresentar o curso e a programação.
What's included
1 video
Este módulo analisa diferentes métodos de carregamento de dados: EL, ELT e ETL e quando usar cada um deles.
What's included
6 videos1 assignment
Este módulo mostra como executar o Hadoop no Dataproc, como usar o Cloud Storage e como otimizar os jobs do Dataproc.
What's included
11 videos1 assignment1 app item
Este módulo aborda o uso do Dataflow para criar pipelines de processamento de dados.
What's included
13 videos1 assignment6 app items
Este módulo mostra como gerenciar pipelines de dados com o Cloud Data Fusion e o Cloud Composer.
What's included
13 videos1 assignment2 app items
Resumo do curso
What's included
1 video
Instructor
Instructor ratings
5.0 (5 ratings)Offered by
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