Os dois principais componentes de um pipeline de dados são data lakes e warehouses. Neste curso, destacamos os casos de uso para cada tipo de armazenamento e as soluções de data lake e warehouse disponíveis no Google Cloud de forma detalhada e técnica. Além disso, também descrevemos o papel de um engenheiro de dados, os benefícios de um pipeline de dados funcional para operações comerciais e analisamos por que a engenharia de dados deve ser feita em um ambiente de nuvem.
Como criar data lakes e data warehouses no Google Cloud
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Como criar data lakes e data warehouses no Google Cloud
This course is part of Data Engineer, Big Data and ML on Google Cloud em Português Specialization
Instructor: Google Cloud Training
Included with
Gain insight into a topic and learn the fundamentals.
23 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
Diferenciar data lakes de data warehouses.
Conhecer os casos de uso para cada tipo de armazenamento e as soluções de data lake e warehouse disponíveis no Google Cloud.
Entender o papel de um engenheiro de dados e quais os benefícios de um pipeline de dados funcional para as operações comerciais.
Analisar por que a engenharia de dados deve ser feita em um ambiente na nuvem.
Skills you'll gain
Tools you'll learn
Details to know
Shareable certificate
Add to your LinkedIn profile
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 7 modules in this course
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