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Data Engineering on GCP

1h 17m 33s
English
Paid

Course description

Google Cloud Platform (GCP) is one of the most popular cloud platforms in the world, providing an extensive set of tools and services for building, managing, and optimizing data pipelines. GCP enables efficient storage, processing, analysis, and visualization of data, helping data engineers create scalable and high-performance solutions.
Read more about the course

What You Will Learn in the Course

In this practical course, you will step by step create your own project on GCP:

  • Extract data from an external weather API
  • Process it through a pipeline using GCP cloud services
  • Store the data in a server database
  • Create visualizations using Looker Studio

The course will help you master GCP from scratch, and the skills you acquire will also be useful when working with other cloud platforms such as AWS, as many of the services are quite similar.

In addition to the course, you will have access to a GitHub repository with a project overview and ready-made code snippets to help you quickly replicate the training examples.

Course Structure

  • Project Data and Goals
    • We will analyze the pipeline architecture, define the project goals, and get acquainted with the API for obtaining weather data. You will also learn how to set up an account in Google Cloud and activate the necessary services (by the way, Google provides $300 for free platform testing!).
  • Project Preparation
    • Create a project in Google Cloud, activate APIs, and set up schedules for task automation.
  • Pipeline Creation: Extracting Data from API
  • Set up the necessary resources for pipeline operation:
    • A server database MySQL via Cloud SQL
    • A virtual machine based on Linux via Compute Engine for database management
    • Cloud Scheduler for scheduling API calls
    • Server functions for data processing
    • Pub/Sub message queue for data transfer between services
  • Writing Data to the Database
    • Learn to write server functions to store data in MySQL, test the writing process, and ensure that data is stored correctly.
  • Data Visualization
    • Set up Looker Studio to create clear visualizations: build bubble charts, time series, and organize weather data monitoring.

This course will give you practical experience with Google Cloud Platform tools and help develop key skills for working as a data engineer.

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#1: Introduction

All Course Lessons (23)

#Lesson TitleDurationAccess
1
Introduction Demo
01:14
2
GitHub & the team
01:31
3
Architecture of this project
03:20
4
Introduction Weather API
02:19
5
Setup Google Cloud Account
02:13
6
Creating the project
02:36
7
Enabling the required APIs
01:35
8
Configure scheduling
02:21
9
Setup VM for database interaction
02:54
10
Setup mysql database
02:17
11
Setup vm client and create database
02:47
12
Creating pub/sub message queue
01:42
13
Create cloud function to pull data form API
04:18
14
Explanation code pull from API
04:21
15
Create function to write to db
07:48
16
Explanation code write data to db
05:57
17
Testing the function
05:52
18
Create function write data to db - pull
03:54
19
Explanation code write data to db - pull
04:34
20
Setup Looker Studio and create bubble chart
02:21
21
Setup Looker Studio and create time series chart
01:58
22
Pipeline Monitoring
06:21
23
Conclusion & Challenges
03:20

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