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Overview
The Building Modern Data Analytics Solutions on AWS course is designed to equip data professionals with the skills to modernize data architectures using AWS services. Through a combination of instructor-led presentations, hands-on labs, and group exercises, participants will learn to build and operate data analytics pipelines that transform data into actionable insights. The course delves into services such as Amazon Lake Formation, AWS Glue, Amazon EMR, Amazon Kinesis, and Amazon Redshift.
Objectives
By the end of this course, leaner will be able to:
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Leverage AWS data services to store, process, analyze, stream, and query data for informed decision-making at scale.
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Modernize end-to-end data solutions to enhance agility and responsiveness.
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Apply best practices in building and operating data analytics pipelines using AWS services.
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Understand the integration of various AWS services to create comprehensive data analytics solutions.
Prerequisites
Participants should have completed either the AWS Technical Essentials or Architecting on AWS courses. Additionally, completing the Building Data Lakes on AWS course is recommended to gain foundational knowledge beneficial for this course.
Course Outline
Learn to build operational data lakes that support structured and unstructured data using AWS Lake Formation, AWS Glue, and Amazon Athena.
Focus on building analytics solutions with Amazon Redshift, covering data collection, ingestion, cataloging, storage, and processing.
Explore batch processing using Amazon EMR and AWS Glue, emphasizing efficient data ingestion and transformation.
Build streaming analytics solutions using Amazon Kinesis and Amazon MSK for real-time data processing and analysis.
