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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来自BUILDING BATCH DATA PIPELINES ON GCP的热门评论
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
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.
This course really teaches me in-depth about data engineering than the cloud or any other products offered by GCP which is the most important part.
Good introduction to pipelines building in GCP, Starting labs need to be in more detail. Other than that very good course.