Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Dataflow, and how to store processed records to BigQuery or Bigtable for analysis. Learners get hands-on experience building streaming data pipeline components on Google Cloud by using Google Cloud Skills Boost.
Overview
Syllabus
- Introduction
- This module introduces the course and agenda
- Introduction to Processing Streaming Data
- This modules talks about challenges with processing streaming data
- Serverless Messaging with Pub/Sub
- This module talks about using Pub/Sub to ingest incoming streaming data
- Dataflow Streaming Features
- This module revisits Dataflow and focuses on its streaming data processing capabilities
- High-Throughput BigQuery and Bigtable Streaming Features
- This modules covers BigQuery and Bigtable for streaming data
- Advanced BigQuery Functionality and Performance
- This module dives into more advanced features of BigQuery
- Summary
- This module recaps the topics covered in course
Taught by
Google Cloud Training
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