ETL using Python: from MySQL to BigQuery
ETL using Python: from MySQL to BigQuery, available at $49.99, has an average rating of 4.45, with 27 lectures, based on 384 reviews, and has 3023 subscribers.
You will learn about 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 This course is ideal for individuals who are Business Intelligence Analysts or Data Analysts or Beginner Data Engineers or Beginner Software Developers or Data Power Users It is particularly useful for Business Intelligence Analysts or Data Analysts or Beginner Data Engineers or Beginner Software Developers or Data Power Users.
Enroll now: ETL using Python: from MySQL to BigQuery
Summary
Title: ETL using Python: from MySQL to BigQuery
Price: $49.99
Average Rating: 4.45
Number of Lectures: 27
Number of Published Lectures: 27
Number of Curriculum Items: 27
Number of Published Curriculum Objects: 27
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will 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
Who Should Attend
- Business Intelligence Analysts
- Data Analysts
- Beginner Data Engineers
- Beginner Software Developers
- Data Power Users
Target Audiences
- Business Intelligence Analysts
- Data Analysts
- Beginner Data Engineers
- Beginner Software Developers
- Data Power Users
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:
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Setup
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Setting up a GCP Account
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Credential and Authentication for security
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Python Environment Setup
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Extract
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Use Python to connect to MySQL
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Use Python’s pandas to export data
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Python library usage for saving files to file paths
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Transform
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Use Python functions to transform data
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Use Python pandas to transform data
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Use inline SQL during Extract for data transformation
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Load
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Use the BigQuery Python library
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Connect to BigQuery
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Load data to BigQuery
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Incremental Loads vs Truncate and Load
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Other data handling options during Load
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After taking this course, you’ll be comfortable with the following pretty cool things:
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Connect to MySQL using Python
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Learn how to obscure your database credentials so you’re not exposing them in your code
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Usage of the os module for the purpose of saving files and hard coding fewer things.
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Use both Python and the pandas library to transform data on the fly during the Transformation phase of your ETL
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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!
Course Curriculum
Chapter 1: Setup
Lecture 1: Introduction
Lecture 2: Installing Python
Lecture 3: Virtual Environments
Lecture 4: Creating a Google Account
Lecture 5: BigQuery Project, Dataset and Tables
Lecture 6: Installing the Google SDK
Lecture 7: Google Authentication
Lecture 8: Storing Connection Properties
Lecture 9: Installing Needed Modules
Lecture 10: ETL Overview
Chapter 2: Extract
Lecture 1: Connect to MySQL
Lecture 2: Query MySQL using Python
Lecture 3: Overview of Pandas
Lecture 4: Pandas dtypes
Lecture 5: Pandas filters
Lecture 6: Pandas Export to CSV
Chapter 3: Transform
Lecture 1: Pandas new column with SQL
Lecture 2: Pandas new column with Python Function
Lecture 3: Pandas data transformation
Chapter 4: Load
Lecture 1: BigQuery Console: Create Table DDL
Lecture 2: BigQuery Console: Create Table file upload
Lecture 3: BigQuery: Connect with Python
Lecture 4: BigQuery: Loading Data
Lecture 5: BigQuery: Truncate v Append
Lecture 6: Big Query: Complete ETL Program
Lecture 7: BigQuery: Bonus Material
Chapter 5: Final Thoughts
Lecture 1: Final Thoughts and Other Resources
Instructors
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Oscar Valles
Analytics and Business Intelligence Professional
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 11 votes
- 3 stars: 63 votes
- 4 stars: 132 votes
- 5 stars: 176 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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