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Data Engineering with Google Dataflow and Apache Beam
First steps to Extract, Transform and Load data using Apache Beam and Deploy Pipelines on Google Dataflow
Lectures -21
Duration -2 hours
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Course Description
This course wants to introduce you to the Apache Foundation's newest data pipeline development framework: The Apache Beam, and how this feature is becoming popular in partnership with Google Dataflow. In a summary, we want to cover the following topics:
1. Understand your inner workings
2. What are your benefits
3. Explain how to use on your local machine without installation via Google Colab for development
4. Its main functions
5. Configure Apache Beam python SDK locallyvice
6. How to deploy this resource on Google Dataflow to a Batch pipeline
This course is dynamic, you will be receiving updates whenever possible.
It is important to remember that this course does not teach Python, but uses it. So, get comfortable with knowing Python basics, defining a function, creating objects and data types.
Also, if you are interested in learning section 4, which consists of deploying a pipeline on Google Dataflow, you will need to have a free counter in GCP. It's a simple process, but it requires a credit card!
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Schedule:
· Section 2 – Concepts
· Section 3 – Main Functions
· Section 4 – Apache Beam on Google Dataflow
Goals
What will you learn in this course:
- Apache Beam
- AETL
- Python
- Google Cloud
- DataFlow
- Google Cloud Storage
Prerequisites
What are the prerequisites for this course?
- Basic Python
- Python running on machine and above 3.7
- Free GCP account
Curriculum
Check out the detailed breakdown of what’s inside the course
Apache Beam Concepts
3 Lectures
- 2.1 What is Apache Beam ? 02:23 02:23
- 2.2 Apache Beam Architecture Overview 03:46 03:46
- 2.3 Apache Beam Pipeline Flow 06:44 06:44
Apache Beam Main Functions
10 Lectures
Batch Dataflow Pipelines
8 Lectures
Instructor Details
Cassio Alessandro deBolba
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