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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/streaming-analytics-systems-gcp
课程评论：没有评论
课程名称：在谷歌云上构建弹性流数据分析系统 概述：处理流数据正变得越来越受欢迎，因为流处理使企业能够实时获取业务运营的指标。本课程讲解如何在谷歌云上构建流数据管道。课程中介绍了如何使用Pub/Sub处理传入的流数据，并讨论了如何利用Dataflow对流数据进行聚合和转换，最终将处理后的记录存储到BigQuery或Cloud Bigtable进行分析。学习者将通过QwikLabs获得在谷歌云上构建流数据管道组件的实际操作经验。 教学大纲： 1. 介绍 - 本模块介绍了课程和议程。 2. 流数据处理简介 - 本模块讨论了流数据处理所面临的挑战。 3. 使用Pub/Sub进行无服务器消息传递 - 本模块讲解如何使用Pub/Sub来接收进入的流数据。 4. Dataflow流处理功能 - 本模块重新审视Dataflow，并着重介绍其流数据处理能力。 5. 支持高吞吐量的BigQuery和Bigtable流处理功能 - 本模块介绍BigQuery和Bigtable在流数据处理中的应用。 6. 高级BigQuery功能与性能 - 本模块深入探讨了BigQuery的更高级功能。 7. 总结 - 本模块回顾课程中涵盖的主题。
Name:Introduction
Description:This module introduces the course and agenda
Name:Introduction to Processing Streaming Data
Description:This modules talks about challenges with processing streaming data
Name:Serverless Messaging with Pub/Sub
Description:This module talks about using Pub/Sub to ingest incoming streaming data
Name:Dataflow Streaming Features
Description:This module revisits Dataflow and focuses on its streaming data processing capabilities
Name:High-Throughput BigQuery and Bigtable Streaming Features
Description:This modules covers BigQuery and Bigtable for streaming data
Name:Advanced BigQuery Functionality and Performance
Description:This module dives into more advanced features of BigQuery
Name:Summary
Description:This module recaps the topics covered in course
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.
