Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
ETL using Python: from MySQL to BigQuery
Highest Rated
Rating: 4.6 out of 5(888 ratings)
5,664 students

ETL using Python: from MySQL to BigQuery

A course for supercharged analysts
Created byOscar Valles
Last updated 4/2026
English

What you'll learn

  • Connect to MySQL using Python
  • Connect to BigQuery using Python
  • ETL data from MySQL to BigQuery using Python
  • Setting up their environment to use Python with MySQL and BigQuery

Course content

5 sections27 lectures2h 58m total length
  • Introduction5:07
  • Installing Python3:17
  • Virtual Environments5:32
  • Creating a Google Account3:37
  • BigQuery Project, Dataset and Tables6:20
  • Installing the Google SDK7:58
  • Google Authentication1:52
  • Storing Connection Properties3:15

    Please note, connection properties have been updated:

    host: 82.197.82.63

    username: u479841347_user

    password: LearnSQL123

    database: u479841347_sql_course

    port: 3306

  • Installing Needed Modules7:02
  • ETL Overview4:06

Requirements

  • Python installed (e.g. virtual environment, anaconda, etc...)
  • Familiarity with SQL
  • Familiarity with Python
  • GCP Account for BigQuery Access
  • An IDE like VS Code or PyCharm

Description

This is a direct and to the point course that will get you quickly ETL'ing data from MySQL to BigQuery.

The lessons in this course are broken out into short How-Tos. Therefore you can take this course over the weekend and be ready to show off your skills on Monday morning!

Things that we will cover:

  • Setup

    • Setting up a GCP Account

    • Credential and Authentication for security

    • Python Environment Setup

  • Extract

    • Use Python to connect to MySQL

    • Use Python's pandas to export data

    • Python library usage for saving files to file paths

  • Transform

    • Use Python functions to transform data

    • Use Python pandas to transform data

    • Use inline SQL during Extract for data transformation

  • Load

    • Use the BigQuery Python library

    • Connect to BigQuery

    • Load data to BigQuery

    • Incremental Loads vs Truncate and Load

    • Other data handling options during Load

After taking this course, you'll be comfortable with the following pretty cool things:

  • Connect to MySQL using Python

  • Learn how to obscure your database credentials so you're not exposing them in your code

  • Usage of the os module for the purpose of saving files and hard coding fewer things.

  • Use both Python and the pandas library to transform data on the fly during the Transformation phase of your ETL

  • Learn how to use GBQ's modules/libraries to make the loading of the data a very easy, straightforward task

Have fun, enjoy and keep growing!

Who this course is for:

  • Business Intelligence Analysts
  • Data Analysts
  • Beginner Data Engineers
  • Beginner Software Developers
  • Data Power Users