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ETL Using Python: From MySQL to BigQuery

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Last updated 5/2022 English
Overview

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

  1. Setting up a GCP Account
  2. Credential and Authentication for security
  3. Python Environment Setup

Extract

  1. Use Python to connect to MySQL
  2. Use Python's pandas to export data
  3. Python library usage for saving files to file paths

Transform

  1. Use Python functions to transform data
  2. Use Python pandas to transform data
  3. Use inline SQL during Extract for data transformation

Load

  1. Use the BigQuery Python library
  2. Connect to BigQuery
  3. Load data to BigQuery
  4. Incremental Loads vs Truncate and Load
  5. Other data handling options during Load

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

  1. Connect to MySQL using Python
  2. Learn how to obscure your database credentials so you're not exposing them in your code
  3. Usage of the OS module for the purpose of saving files and hard coding fewer things.
  4. Use both Python and the pandas library to transform data on the fly during the Transformation phase of your ETL
  5. 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
  1. Business Intelligence Analysts
  2. Data Analysts
  3. Beginner Data Engineers
  4. Beginner Software Developers
  5. Data Power Users
What you'll learn
  1. Connect to MySQL using Python
  2. Connect to BigQuery using Python
  3. ETL data from MySQL to BigQuery using Python
  4. Setting up their environment to use Python with MySQL and BigQuery
Requirements
  1. Having Python Installed, preferably using a virtual environment
  2. An IDE like VS Code or PyCharm
  3. GCP Account for BigQuery Access
  4. Familiar with Python
  5. Familiar with SQL