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.
EL, ELT, ETL
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Reviews
4.5 (1,597 ratings)
- 5 stars65.30%
- 4 stars25.92%
- 3 stars6.32%
- 2 stars1.56%
- 1 star0.87%
AS
May 19, 2020
Informative on various features. But cloud fusion and dataflow are not very clearly explained in detail.. expecting more on this. Want to learn more on the pipeline topic please.
SV
Jun 18, 2020
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.
From the lesson
Introduction to Building Batch Data Pipelines
This module reviews different methods of data loading: EL, ELT and ETL and when to use what
Taught By
Google Cloud Training
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