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 for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
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- 5 stars65,09 %
- 4 stars26,14 %
- 3 stars6,24 %
- 2 stars1,60 %
- 1 star0,90 %
Principales reseñas sobre BUILDING BATCH DATA PIPELINES ON GOOGLE CLOUD
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
Excellent course with appropriate explanation on cloud data fusion, data composer, data proc and cloud data-flow. Must learn course for all aspiring Big Data Engineers.
Good introduction to pipelines building in GCP, Starting labs need to be in more detail. Other than that very good course.
Good course covering Dataproc, Dataflow, Dataprep and the labs ofcourse..
great way to get introduced to batch data pipelines in GCP.
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