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Master AWS Data Analytics with hands-on practice!. Prepare for the AWS Certified Data Analytics Specialty (2023) exam with this comprehensive course. Gain expertise in data collection, storage, processing, and analysis using AWS services like Kinesis, S3, DynamoDB, and more, with practical, hands-on exercises.
Instructor: Packt - Course Instructors
Included with
Recommended experience
Beginner level
Ideal for data engineers, analysts, and IT pros seeking AWS data analytics skills. Basic AWS knowledge recommended.
Recommended experience
Beginner level
Ideal for data engineers, analysts, and IT pros seeking AWS data analytics skills. Basic AWS knowledge recommended.
Create scalable data pipelines using Amazon Kinesis and SQS
Apply optimized data storage and management techniques with S3 and DynamoDB
Analyze and visualize complex datasets using Amazon Athena and QuickSight
Implement AWS security best practices to ensure robust data protection
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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.
Applied Learning Project
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.
Set up and manage data pipelines using Kinesis and S3 for real-time data processing
Implement S3 security features, including encryption and bucket policies, to ensure data protection
Configure and apply lifecycle policies, replication, and versioning in S3 for efficient data management
Optimize DynamoDB throughput and analyze methods for managing large datasets
Integrate and scale data pipelines using AWS Lambda and Glue for efficient data processing
Analyze real-time data streams with Kinesis Analytics and OpenSearch to gain actionable insights
Implement security measures and manage data workflows for high-performance analysis
Analyze real-time data streams with Kinesis Analytics and OpenSearch to gain actionable insights
Create and customize dashboards using Amazon QuickSight for effective data visualization
Implement AWS security practices, including encryption and key management, to safeguard cloud environments
Configure CloudTrail and VPC endpoints to secure AWS environments and ensure compliance
Integrate AWS services to build robust, secure, and scalable cloud infrastructure
Packt helps tech professionals put software to work by distilling and sharing the working knowledge of their peers. Packt is an established global technical learning content provider, founded in Birmingham, UK, with over twenty years of experience delivering premium, rich content from groundbreaking authors on a wide range of emerging and popular technologies.
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This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
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