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.
À propos de ce cours
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Meilleurs avis pour BUILDING BATCH DATA PIPELINES ON GOOGLE CLOUD
Thank you very much the team. Course content and materials are at the higher appreciation level. really enjoyed and satisfied.
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
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.
takes time understand , video makes little bore but in practice to enjoy doing but try to mention required time for excuetion or waiting time to task to executeto ece
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