The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment.
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Acerca de este Curso
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Prueba Coursera para negociosQué aprenderás
Differentiate between data lakes and data warehouses.
Explore use-cases for each type of storage and the available data lake and warehouse solutions on Google Cloud.
Discuss the role of a data engineer and the benefits of a successful data pipeline to business operations.
Examine why data engineering should be done in a cloud environment.
¿Podría tu empresa beneficiarse de la capacitación de los empleados en las habilidades más demandadas?
Prueba Coursera para negociosOfrecido por
Programa - Qué aprenderás en este curso
Introduction
Introduction to Data Engineering
Building a Data Lake
Building a data warehouse
Summary
Reseñas
- 5 stars72,71 %
- 4 stars22,89 %
- 3 stars3,30 %
- 2 stars0,75 %
- 1 star0,33 %
Principales reseñas sobre MODERNIZING DATA LAKES AND DATA WAREHOUSES WITH GOOGLE CLOUD
In depth course explaining how to build scalable & state of the art data lakes & data warehouse on GCS, CloudSQL, Bigquery. Ways to optimize bigquery & improve the schema
A better understanding of BigQuery starts here. A vital resource for consultants, data analysts, and product managers, and an important reference source for engineers and data scientists.
Course material spends a little too much time promoting the benefits of GCP when it could be focusing on the technical aspects of using GCP
The labs were awesome! The trainers in the video and in the demo were well prepared. The quizes however were short and not well thoughtful.
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