Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud Platform for data transformation including BigQuery, executing Spark on Cloud Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Cloud Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud Platform using QwikLabs.
Этот курс входит в специализацию ''Профессиональная сертификация 'Data Engineering with Google Cloud''
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Google Cloud
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Программа курса: что вы изучите
Introduction
In this module, we introduce the course and agenda
Introduction to Batch Data Pipelines
This module reviews different methods of data loading: EL, ELT and ETL and when to use what
Executing Spark on Cloud Dataproc
This module shows how to run Hadoop on Cloud Dataproc, how to leverage GCS, and how to optimize your Dataproc jobs.
Manage Data Pipelines with Cloud Data Fusion and Cloud Composer
This module shows how to manage data pipelines with Cloud Data Fusion and Cloud Composer.
Serverless Data Processing with Cloud Dataflow
This module covers using Cloud Dataflow to build your data processing pipelines
Summary
This module reviews the topics covered in this course
Рецензии
Лучшие отзывы о курсе BUILDING BATCH DATA PIPELINES ON GCP
There were some minor problem and mistake in the lab file. The python/java scripts were not explained at all. There are questions about the code itself, but then the questions were not answered.
A great course to help understand the various wonderful options Google Cloud has to offer to move on-premise Hadoop workload to Google Cloud Platform to leverage scalability of clusters.
Great course learning what it is the big advantages of using GCP for data given they have big implementations and with better performance of what it is today in on premises scenarios
Informative on various features. But cloud fusion and dataflow are not very clearly explained in detail.. expecting more on this. Want to learn more on the pipeline topic please.
Профессиональная сертификация 'Data Engineering with Google Cloud': общие сведения
87% of Google Cloud certified users feel more confident in their cloud skills. This program provides the skills you need to advance your career, and training to support your preparation for the industry-recognized Google Cloud Associate Cloud Engineer certification.

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