[PS] AWS Certified Data Engineer – Associate (DEA-C01): Data Ingestion and Transformation Course (Jan 2025) + Files

Mastering AWS Data Ingestion and Transformation for Certification
The AWS Certified Data Engineer – Associate (DEA-C01): Data Ingestion and Transformation Course will be your key to passing the AWS Certified Data Engineer -Associate (DEA-C01) certification exam in the area of Data Ingestion and Transformation. Since this area is approximately 34 percent of the exam content, the course gives you specific and intense training in order to be able to pass. The content of the course is over 6 hours of video-based content led by instructor Beth Hord, where you will learn the most important AWS services, real-life applications, and how to deploy effective and reliable data pipelines.

Building Scalable ETL and ELT Pipelines on AWS
You will explore different data ingestion tools such as Amazon Kinesis, AWS Glue, Lambda, and Redshift in order to deep dive into different ways of ingesting data in batch mode or real-time streaming. The course provides you with the knowledge to build ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) workflows capable of consuming the APIs, streams, and object storage like Amazon S3. The implementation focus is not only highlighted, but also on performance, scalability, and cost-efficiency optimization, which is vital in production environments.

Practical Skills for Real-World Data Engineering
Outside of infrastructure, the AWS Certified Data Engineer – Associate (DEA-C01): Data Ingestion and Transformation Course has also taught fundamental data engineering skills to work in the real world, including SQL querying with joins, aggregations, and window functions. You will also learn how you can use containers or serverless compute in your pipelines, and how you can use infrastructure-as-code tools to automate deployments. However, you will not only be ready to take the DEA-C01 certification exam by the end of the course, but you will also be ready to address the life problems of data transformation with the help of AWS.