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
Good, I think pipelines need to have more labs related to some necessities in the industry, such as connect them to other external sources outside 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.
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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