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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- 4 stars26.23%
- 3 stars6.31%
- 2 stars1.62%
- 1 star0.91%
BUILDING BATCH DATA PIPELINES ON GOOGLE CLOUD からの人気レビュー
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.
Interesting topics, but some of the labs are a waste of time (1 minute of hands-on experience, 30 minutes of provisioning resources and pipeline execution).
Thank you very much the team. Course content and materials are at the higher appreciation level. really enjoyed and satisfied.
Some parts of the course where not explained in full detail, especially some qwuick labs where questions were not tested or even provided with answers