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Building Resilient Streaming Analytics Systems on Google Cloud

Google Cloud via Coursera

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Overview

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.

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

Reviews

4.6 rating at Coursera based on 1250 ratings

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