基于Google云平台的弹性流媒体分析系统构建

Building Resilient Streaming Analytics Systems on GCP

663 次查看
Google 云端平台
Coursera
  • 完成时间大约为 13 个小时
  • 中级
  • 英语
注:本课程由Coursera和Linkshare共同提供,因开课平台的各种因素变化,以上开课日期仅供参考

课程概况

*Note: this is a new course with updated content from what you may have seen in the previous version of this Specialization.

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 Platform. Cloud Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Cloud 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 Platform using QwikLabs.

课程大纲

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 Cloud Pub/Sub

This module talks about using Cloud Pub/Sub to ingest incoming streaming data

Cloud Dataflow Streaming Features

This module revisits Cloud 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

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