借助Google云平台实现数据湖和数据仓库的现代化

Modernizing Data Lakes and Data Warehouses with GCP

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Google 云端平台
Coursera
  • 完成时间大约为 12 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

The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud Platform in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment. Learners will get hands-on experience with data lakes and warehouses on Google Cloud Platform using QwikLabs.

课程大纲

Introduction

This module gives an introduction of the Data Engineering specialization and the course.

Introduction to Data Engineering

This module describes the role of a data engineer and motivates the claim why data engineering should be done in the Cloud

Building a Data Lake

In this module, we describe what data lake is and how to use Google Cloud Storage as you data lake on GCP

Building a data warehouse

In this module, we talk about BigQuery as a data warehousing option on GCP

Summary

This module reviews all the topics covered in the course

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