Data Science on Google Cloud Platform: Building Data Pipelines

Learn how to design and build big data pipelines on Google Cloud Platform.

Introduction

• What goes into a data pipeline?
• Data science modules covered

1. GCP Data Pipeline Products

• GCP data pipeline options
• Cloud Dataproc
• Cloud Dataflow
• Cloud Pub/Sub

2. Apache Beam

• What is Apache Beam?
• Beam pipelines
• PCollections
• Transforms
• Pipeline I/O
• Runners

3. Setting Up Dataflow

• Setting up GCP for Dataflow
• Setting up Python
• Creating a simple pipeline
• Executing in Dataflow

4. Data Processing with Beam and Dataflow

• Reading text files
• ParDo
• GroupBy
• Map
• Combine
• Writing data to text files
• Other capabilities

5. Cloud Pub/Sub

• What is Pub/Sub?
• Topics and messages
• Publishers
• Subscribers
• Create a topic
• Create a subscription
• Publish and receive
• Python SDK

6. Streaming with Dataflow

• Streaming with Dataflow
• Windowing with Dataflow
• Streaming and windowing example

Conclusion

• Next steps