MP4 | Video: h264, 1280×720 | 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
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