ETL using Python: from MySQL to BigQuery
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 27 lectures (2h 57m) | Size: 870.7 MB

A course for supercharged analysts
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

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.