In this course, you'll embark on a journey to master AWS services essential for passing the AWS Certified Data Analytics Specialty exam. Starting with data collection, you’ll work with tools like Amazon Kinesis and SQS to ingest and manage real-time data streams. Through hands-on labs, you’ll build scalable data pipelines and gain practical experience with data ingestion strategies. This knowledge is immediately applicable to professional environments, giving you valuable experience with AWS services.
Next, you'll explore AWS data storage and processing using Amazon S3, DynamoDB, and Redshift. Case studies will help you implement storage strategies, optimize performance, and ensure security. You'll simulate real-world scenarios to manage and query data efficiently, preparing you for complex projects. With this expertise, you'll design scalable and secure data architectures on AWS.
Finally, you'll work with Amazon QuickSight, OpenSearch, and Athena to analyze and visualize data. By course completion, you'll be ready for the AWS exam with hands-on skills to apply in real-world scenarios. This makes it an ideal course for data engineers, analysts, and IT professionals aiming to enhance their expertise in AWS data analytics. A basic understanding of AWS services is recommended for this course.
Praktisches Lernprojekt
Learners will build scalable data pipelines using Amazon Kinesis, SQS, and S3, and apply these skills to solve real-world problems such as populating an S3 data lake from EC2 server data. Through hands-on projects, they will implement AWS services like DynamoDB, Redshift, and QuickSight, simulating authentic scenarios to optimize data storage, processing, and visualization.
