課程信息
4.7
1,310 個評分
101 個審閱

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為7 小時

建議:1 week of study, 6-8 hours/week...

英語(English)

字幕:英語(English)

您將獲得的技能

BigqueryBigtableDataflowPublish–Subscribe Pattern

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為7 小時

建議:1 week of study, 6-8 hours/week...

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 1 小時

Module 1: Architecture of Streaming Analytics Pipelines

...
5 個視頻 (總計 39 分鐘), 1 個閱讀材料, 1 個測驗
5 個視頻
Challenge #1: Variable volumes require ability of ingest to scale and be fault-tolerant4分鐘
Challenge #2 : Latency is to be expected5分鐘
Challenge #3 : Need instant insights6分鐘
Discuss some streaming scenarios8分鐘
1 個閱讀材料
Lab Worksheet10分鐘
1 個練習
Module 1 Quiz4分鐘
完成時間為 2 小時

Module 2: Ingesting Variable Volumes

...
4 個視頻 (總計 34 分鐘), 2 個測驗
4 個視頻
How it works: Topics and Subscriptions14分鐘
Lab Overview34
Lab demo and review8分鐘
1 個練習
Module 2 Quiz8分鐘
完成時間為 2 小時

Module 3: Implementing Streaming Pipelines

...
6 個視頻 (總計 70 分鐘), 2 個測驗
6 個視頻
Challenges in stream processing14分鐘
Build a stream processing pipeline for live traffic data11分鐘
Handle late data: watermarks, triggers, accumulation14分鐘
Lab overview35
Lab demo and review15分鐘
1 個練習
Module 3 Quiz2分鐘
完成時間為 1 小時

Module 4: Streaming analytics and dashboards

...
3 個視頻 (總計 20 分鐘), 2 個測驗
3 個視頻
Lab overview45
Lab demo and review5分鐘
1 個練習
Module 4 Quiz4分鐘
完成時間為 2 小時

Module 5: Handling Throughput and Latency Requirements

...
8 個視頻 (總計 63 分鐘), 1 個閱讀材料, 2 個測驗
8 個視頻
Bigtable: big, fast, autoscaling NoSQL4分鐘
Ingesting into Bigtable4分鐘
Designing for Bigtable23分鐘
Streaming into Bigtable1分鐘
Lab demo and review4分鐘
Performance considerations6分鐘
Summary of Data Engineering on GCP Specialization8分鐘
1 個閱讀材料
Cloud Bigtable Streaming10分鐘
1 個練習
Module 5 Quiz6分鐘
4.7
101 個審閱Chevron Right

38%

完成這些課程後已開始新的職業生涯

37%

通過此課程獲得實實在在的工作福利

15%

加薪或升職

熱門審閱

創建者 PGAug 25th 2018

This course was very helpful to understand how to built high throughput streaming work flows on google cloud. It described in detail how to model big table for efficient application.

創建者 CCAug 19th 2017

Course gives nice overview of Bigtable, when to use it compared to bigquery. flowchart describing the when to use which product is really helpful. Thanks Lak for the course.

關於 Google 云端平台

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success....

關於 Data Engineering on Google Cloud Platform 專項課程

This five-week, accelerated online specialization provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. The course covers structured, unstructured, and streaming data. This course teaches the following skills: • Design and build data processing systems on Google Cloud Platform • Leverage unstructured data using Spark and ML APIs on Cloud Dataproc • Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow • Derive business insights from extremely large datasets using Google BigQuery • Train, evaluate and predict using machine learning models using Tensorflow and Cloud ML • Enable instant insights from streaming data This class is intended for developers who are responsible for: • Extracting, Loading, Transforming, cleaning, and validating data • Designing pipelines and architectures for data processing • Creating and maintaining machine learning and statistical models • Querying datasets, visualizing query results and creating reports >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<...
Data Engineering on Google Cloud Platform

常見問題

  • 是的,您可以在注册之前预览第一个视频和查看授课大纲。您必须购买课程,才能访问预览不包括的内容。

  • 如果您决定在班次开始日期之前注册课程,那么您将可以访问课程的所有课程视频和阅读材料。班次开始之后,您便可以提交作业。

  • 在您注册且班次开课之后,您将可以访问所有视频和其他资源,包括阅读材料内容和课程论坛。您将能够查看和提交练习作业,并完成所需的评分作业以获得成绩和课程证书。

  • 如果您成功完成课程,您的电子课程证书将添加到您的成就页中,您可以通过该页打印您的课程证书或将其添加到您的领英档案中。

  • 该课程是 Coursera 上提供的为数不多的课程之一,目前只对已购买课程或已获得助学金的学生开放。

還有其他問題嗎?請訪問 學生幫助中心