PySpark and AWS: Master Big Data with PySpark and AWS - Project Architecture

The video tutorial guides viewers through designing a data architecture using AWS services. It begins with an introduction to creating an architecture with RDS and S3, followed by an overview of AWS Data Migration Service (DMS) and its endpoints. The tutorial then explains how to use AWS Lambda functions and PySpark jobs in AWS Glue for data processing. Finally, it covers the implementation of Change Data Capture (CDC) to manage ongoing data changes in a MySQL database, emphasizing the importance of CDC in modern data pipelines.

What steps are involved in the full load process described?

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What happens when a file lands in the S3 bucket?

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What are the potential changes that can be captured in the MySQL database?

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Discuss the importance of the CDC pipeline in the context of AWS and PySpark.

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