Aws Data Engineering Services (glue, Athena, Redshift) Training Course: Aws Data Mastery

Introduction

Unlock the full potential of your data with our AWS Data Engineering Services (Glue, Athena, Redshift) Training Course. This program is designed to equip you with the essential skills to utilize AWS services for data processing and storage, enabling you to build scalable and efficient data solutions. In today's data-driven world, mastering AWS data engineering tools is crucial for organizations seeking to derive actionable insights from their data. Our AWS data engineering training course offers hands-on experience and expert guidance, empowering you to leverage AWS Glue, Athena, and Redshift for diverse data engineering tasks.

This AWS data mastery training delves into the core concepts of AWS data engineering, covering topics such as ETL processes, data warehousing, and serverless querying. You'll gain expertise in using industry-standard AWS services to utilize AWS services for data processing and storage, meeting the demands of modern data-intensive organizations. Whether you're a data engineer, data architect, or cloud developer, this AWS Data Engineering Services (Glue, Athena, Redshift) course will empower you to design and implement high-performance data solutions on the AWS platform.

Target Audience:

• Data Engineers
• Data Architects
• Cloud Developers
• Data Analysts
• Database Administrators
• Business Intelligence Developers
• Anyone needing AWS data engineering skills

Course Objectives:

• Understand the fundamentals of AWS data engineering services (Glue, Athena, Redshift).
• Master AWS Glue for ETL and data integration.
• Utilize AWS Athena for serverless querying and data analysis.
• Implement AWS Redshift for data warehousing and business intelligence.
• Design and build scalable data pipelines with AWS services.
• Optimize AWS data services for performance and cost-effectiveness.
• Troubleshoot and address common challenges in AWS data engineering.
• Implement data security and access control in AWS data services.
• Integrate AWS data services with other AWS and third-party tools.
• Understand how to handle large datasets and data warehousing in AWS.
• Explore advanced AWS data engineering features (e.g., Glue Streaming, Redshift Spectrum).
• Apply real world use cases for AWS data engineering services.
• Leverage AWS's ecosystem for efficient data engineering workflows.

Duration

10 Days

Course content

Module 1: Introduction to AWS Data Engineering Services

• Fundamentals of AWS data engineering services (Glue, Athena, Redshift).
• Overview of ETL, serverless querying, and data warehousing on AWS.
• Setting up an AWS data engineering development environment.
• Introduction to AWS Glue, Athena, and Redshift.
• Best practices for AWS data engineering.

Module 2: AWS Glue for ETL and Data Integration

• Mastering AWS Glue for ETL and data integration.
• Utilizing Glue jobs, crawlers, and data catalogs.
• Designing and building ETL pipelines with Glue.
• Optimizing Glue jobs for performance and scalability.
• Best practices for AWS Glue.

Module 3: AWS Athena for Serverless Querying

• Utilizing AWS Athena for serverless querying and data analysis.
• Implementing SQL queries on S3 data.
• Designing and building data analysis workflows with Athena.
• Optimizing Athena queries for cost efficiency.
• Best practices for AWS Athena.

Module 4: AWS Redshift for Data Warehousing

• Implementing AWS Redshift for data warehousing and business intelligence.
• Utilizing Redshift clusters and data loading techniques.
• Designing and building data warehouses with Redshift.
• Optimizing Redshift queries for analytical workloads.
• Best practices for AWS Redshift.

Module 5: Scalable Data Pipelines with AWS

• Designing and building scalable data pipelines with AWS services.
• Implementing data ingestion, transformation, and loading (ETL).
• Utilizing AWS Step Functions and Lambda for pipeline orchestration.
• Optimizing pipelines for large-scale data processing.
• Best practices for data pipelines.

Module 6: Performance and Cost Optimization

• Optimizing AWS data services for performance and cost-effectiveness.
• Utilizing performance tuning and monitoring tools.
• Implementing data partitioning and compression strategies.
• Designing cost-effective data solutions.
• Best practices for optimization.

Module 7: Troubleshooting AWS Data Engineering

• Debugging common challenges in AWS data engineering.
• Analyzing AWS service logs and error messages.
• Utilizing troubleshooting techniques for problem resolution.
• Resolving common data engineering issues.
• Best practices for troubleshooting.

Module 8: Data Security and Access Control

• Implementing data security and access control in AWS data services.
• Utilizing IAM roles and policies for data access.
• Designing and building secure data solutions.
• Optimizing security for data protection.
• Best practices for security.

Module 9: Integration with AWS and Third-Party Tools

• Integrating AWS data services with other AWS and third-party tools.
• Utilizing AWS S3, EMR, and QuickSight.
• Implementing data integration with external data sources.
• Optimizing integration for data retrieval and analysis.
• Best practices for integration.

Module 10: Large Datasets and Data Warehousing

• Understanding how to handle large datasets and data warehousing in AWS.
• Utilizing Redshift Spectrum for external data querying.
• Implementing data partitioning and parallel processing.
• Designing scalable data warehousing solutions.
• Best practices for large datasets.

Module 11: Advanced AWS Data Engineering Features

• Exploring advanced AWS data engineering features (Glue Streaming, Redshift Spectrum).
• Utilizing Glue Streaming for real-time data processing.
• Implementing Redshift Spectrum for querying S3 data.
• Designing and building advanced data engineering solutions.
• Optimizing advanced techniques for specific applications.
• Best practices for advanced features.

Module 12: Real-World Use Cases

• Implementing AWS data engineering for real-time analytics and monitoring.
• Utilizing AWS data services for data warehousing and business intelligence.
• Implementing AWS data engineering for machine learning and data science.
• Utilizing AWS data engineering for log processing and data analysis.
• Best practices for real-world applications.

Module 13: AWS Data Engineering Tools Implementation

• Utilizing AWS data engineering tools and frameworks (CloudFormation, CDK).
• Implementing data pipelines with specific tools.
• Designing and building automated data workflows.
• Optimizing tool usage for efficient development.
• Best practices for tool implementation.

Module 14: Performance Monitoring and Logging

• Implementing performance monitoring and logging for AWS data services.
• Utilizing CloudWatch and other monitoring tools.
• Designing and building performance dashboards.
• Optimizing monitoring for real-time insights.
• Best practices for monitoring.

Module 15: Future Trends in AWS Data Engineering

• Emerging trends in AWS data engineering.
• Utilizing AI for data pipeline automation.
• Implementing data mesh architectures on AWS.
• Best practices for future applications.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.