Chapter 3Designing Data Pipelines
Google Cloud Professional Data Engineer Exam objectives covered in this chapter include the following:
- Designing data processing systems
- ✔ 1.2 Designing data pipelines. Considerations include:
- Data publishing and visualization (e.g., BigQuery)
- Batch and streaming data (e.g., Cloud Dataflow, Cloud Dataproc, Apache Beam, Apache Spark and Hadoop ecosystem, Cloud Pub/Sub, Apache Kafka)
- Online (interactive) vs. batch predictions
- Job automation and orchestration (e.g., Cloud Composer)
- ✔ 1.2 Designing data pipelines. Considerations include:
- Building and operationalizing data processing systems
- ✔ 2.2 Building and operationalizing pipelines. Considerations include:
- Data cleansing
- Batch and streaming
- Transformation
- Data acquisition and import
- Integrating with new ...
- ✔ 2.2 Building and operationalizing pipelines. Considerations include:
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