AWS Data Engineering

Categories: AWS, Cloud, Technologies
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About Course

AWS Data Engineering is designed to teach you how to use Amazon Web Services (AWS) tools to architect and manage large-scale data storage and processing solutions. In this course, you will learn how to build data lakes, perform real-time data streaming, and work with AWS data analytics services such as Amazon Redshift, AWS Glue, and Amazon Kinesis. By the end of this course, you’ll have the skills needed to design and maintain big data architectures on AWS.


Why Choose the Course?

  • Learn how to leverage AWS cloud services for building scalable data engineering pipelines.
  • Gain hands-on experience with key AWS data solutions like Redshift, Glue, Kinesis, and Athena.
  • Master techniques for handling big data processing, storage, and analytics.
  • Understand the best practices for security, cost optimization, and data management in AWS.
  • Position yourself for roles such as Data Engineer, Cloud Data Architect, and Big Data Specialist.
  • Prepare for AWS certifications like the AWS Certified Data Analytics – Specialty exam.
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What Will You Learn?

  • Introduction to AWS cloud and its data engineering services.
  • Data storage options on AWS: S3, Redshift, and DynamoDB.
  • Building data lakes and managing ETL (Extract, Transform, Load) pipelines using AWS Glue.
  • Real-time data processing with AWS Kinesis and Lambda.
  • Analytics with Amazon Redshift and Athena for data querying and reporting.
  • Best practices for data security, compliance, and cost management on AWS.
  • Automating data workflows using AWS services like CloudWatch and Step Functions.

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