課程信息
4.6
731 個評分
60 個審閱
專項課程

第 5 門課程(共 5 門),位於

100% 在線

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

可靈活調整截止日期

根據您的日程表重置截止日期。
中級

中級

完成時間(小時)

完成時間大約為7 小時

建議:1 week of study, 6-8 hours/week...
可選語言

英語(English)

字幕:英語(English)...

您將獲得的技能

BigqueryBigtableDataflowPublish–Subscribe Pattern
專項課程

第 5 門課程(共 5 門),位於

100% 在線

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

可靈活調整截止日期

根據您的日程表重置截止日期。
中級

中級

完成時間(小時)

完成時間大約為7 小時

建議:1 week of study, 6-8 hours/week...
可選語言

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(小時)
完成時間為 1 小時

Module 1: Architecture of Streaming Analytics Pipelines

...
Reading
5 個視頻(共 39 分鐘), 1 個閱讀材料, 1 個測驗
Video5 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
Reading1 個閱讀材料
Lab Worksheet10分鐘
Quiz1 個練習
Module 1 Quiz4分鐘
完成時間(小時)
完成時間為 2 小時

Module 2: Ingesting Variable Volumes

...
Reading
4 個視頻(共 34 分鐘), 2 個測驗
Video4 個視頻
How it works: Topics and Subscriptions14分鐘
Lab Overview分鐘
Lab demo and review8分鐘
Quiz1 個練習
Module 2 Quiz8分鐘
完成時間(小時)
完成時間為 2 小時

Module 3: Implementing Streaming Pipelines

...
Reading
6 個視頻(共 70 分鐘), 2 個測驗
Video6 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 overview分鐘
Lab demo and review15分鐘
Quiz1 個練習
Module 3 Quiz2分鐘
完成時間(小時)
完成時間為 1 小時

Module 4: Streaming analytics and dashboards

...
Reading
3 個視頻(共 20 分鐘), 2 個測驗
Video3 個視頻
Lab overview分鐘
Lab demo and review5分鐘
Quiz1 個練習
Module 4 Quiz4分鐘
完成時間(小時)
完成時間為 2 小時

Module 5: Handling Throughput and Latency Requirements

...
Reading
8 個視頻(共 63 分鐘), 2 個測驗
Video8 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
Quiz1 個練習
Module 5 Quiz6分鐘
4.6
60 個審閱Chevron Right
職業方向

67%

完成這些課程後已開始新的職業生涯
工作福利

83%

通過此課程獲得實實在在的工作福利
職業晉升

17%

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 Cloud

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

>>> 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 <<< ***COMPLETION CHALLENGE; receive a GCP t-shirt, see more below.*** This five-week specialization provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. 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 COMPLETION CHALLENGE-Complete any GCP specialization from Oct 23 - Nov 30, 2018 to participate. Check Discussion Forums for full details....
Data Engineering on Google Cloud Platform

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