This class is intended for data analysts, data scientists and programmers who want to build for out-of-the-ordinary scenarios such as high availability, resiliency, high-throughput, real-time streaming analytics on leveraging Google Cloud.
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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 Cloud Bigtable for analysis. Learners will get hands-on experience building streaming data pipeline components on Google Cloud using QwikLabs.
This course is part of the Google Cloud Data Engineer Learning Path Professional Certificate.
What you'll learn
- Interpret use-cases for real-time streaming analytics.
- Manage data events using the Pub/Sub asynchronous messaging service.
- Write streaming pipelines and run transformations where necessary.
- Interoperate Dataflow, BigQuery and Pub/Sub for real-time streaming and analysis
Syllabus
- Introduction
This module introduces the course and agenda.
- Introduction to Processing Streaming Data
This module 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.
- Course Summary
This module recaps the topics covered in course.
- Course Resources
PDF links to all modules.
