- Jupyter
- Dataflow
- Data Pipelines
- Google Cloud Platform
- Real Time Data
- Data Processing
- JSON
- Data Transformation
- Extract, Transform, Load
- SQL
Serverless Data Processing with Dataflow: Develop Pipelines
Completed by Nicolas Rodriguez Celys
December 14, 2021
25 hours (approximately)
Nicolas Rodriguez Celys's account is verified. Coursera certifies their successful completion of Serverless Data Processing with Dataflow: Develop Pipelines
What you will learn
Review the main Apache Beam concepts covered in the Data Engineering on Google Cloud course
Review core streaming concepts covered in DE (unbounded PCollections, windows, watermarks, and triggers)
Select & tune the I/O of your choice for your Dataflow pipeline
Use schemas to simplify your Beam code & improve the performance of your pipeline
Skills you will gain
