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Cassio Alessandro DeBolba
First steps to Extract, Transform and Load data using Apache Beam and Deploy Pipelines on Google Dataflow
Updated on Sep, 2026
Programming, Database and Design Development, Apache Spark
Training 5 or more people ?
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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 summary, we want to cover the following topics:
1. Understand your inner workings
2. What are your benefits
3. Explain how to use it 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!
Check out the detailed breakdown of what’s inside the course
I'm self taught Senior Data Engineer and content creator. Migrated from a machine operator at my 30's to the Data IT Industry. Can help early professionals to drive their path to become data professionals as well as give some great advices for those who wish to live abroad and achieve a sponsorship visa.
My current stack: Data Integration / Processing -> Databricks | Dataflow | AWS Lambdas | Datafusion | DataFactory Automation -> Power Platform | Power Automate | Power Apps Databases -> Snowflake | Big Query | SQL Server Data Transformation -> DBT Versioning / Repository -> Git | Azure DevOps Programming -> SQL | Python | PySpark Cloud Providers -> Azure | GCP | AWS Task / Data Orchestration -> Airflow BI -> Power BI | Qlik Sense CI / CD -> Git Lab CI Containers -> Docker
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