Get AWS Certified Data Analytics Certification
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Experience an immersive and intensive training experience, designed to dive into practical workshops and real case studies.
Learn by doing, and develop concrete skills directly applicable to your future projects.
At the end of your career, we evaluate your acquired skills, issue certification attesting to your expertise, and accompany you to ensure your success in your professional projects.
You are now ready to excel!
Description of the training
This training allows participants to design cloud-based data management solutions using Amazon Web Services database services, such as Amazon RDS, DynamoDB or Aurora, taking into account performance, scalability, availability, security and cost requirements.
Objectives of training
At the end of this training, participants will be able to:
- Master AWS services for Big Data: Amazon S3, Redshift, AWS Glue, Kinesis, Athena, QuickSight.
- Design scalable analytical solutions using AWS services dedicated to data processing and storage.
- Process, integrate, and analyze data from various sources with AWS tools and services.
- Analyze data in real time and create dynamic visualizations with Athena and QuickSight.
- Automate data pipelines with services such as AWS Glue, Kinesis, and Lambda.
- Optimize performance and manage the costs of Big Data solutions on AWS.
Who is this training for?
The training is aimed at a wide audience, including:
- Cloud solutions architects specialized in the design of Big Data and Analytical solutions on AWS.
- Data engineers responsible for data processing and integration in AWS environments.
- Data analysts working on massive data and extracting them for analysis with AWS services.
- Developers and engineers Big Data using services such as Redshift, EMR, Kinesis, Athena, QuickSight.
- Data managers such as the Chief Data Officers (CDOs) responsible for data analysis in the company.
- Consultants and cloud professionals who help companies migrate or design analytical solutions on AWS.
Prerequisites
No specific prerequisites are required. This training is available to anyone wishing to discover AWS, but a basic knowledge of computer science or information systems can be an asset.
Training programme
Introduction aux services de Big Data sur AWS et conception des solutions analytiques
- Overview of Big Data AWS services: S3, Redshift, Kinesis, AWS Glue, Athena, QuickSight.
- Data solution architecture and large-scale analysis in AWS.
- Design of storage architectures (S3), processing (EMR, Glue), and analysis (Athena, Redshift).
- Practice: Designing a data processing architecture with S3 and Glue.
- Processing and processing of data with AWS Glue and Kinesis.
- Practical workshop: Create an ETL pipeline with AWS Glue to clean and load data in Redshift.
- Data analysis with Amazon Athena and visualization with QuickSight.
- Practical workshop: Create interactive dashboards in QuickSight and analyze data in Athena.
- Performance optimization and cost management: Optimization of SQL queries in Redshift and Athena, cost reduction with S3, EMR, Redshift.
- Practical workshop: Optimize a data processing solution in EMR.
- Data security and preparation for the AWS Certified Data Analytics – Specialty exam: Revision of key concepts and white exam to test knowledge.
Training assets
- Pedagogical approach: An alternative between theory and practice for better assimilation of concepts.
- Qualified speakers: Specialist trainers with practical experience in the field of cloud.
- Educational tools and materials: Access to online resources, live demonstrations and real-life case studies.
- Accessibility: Training is open to all, without advanced technical prerequisites.
Pedagogical methods and tools used
- Live demonstrations with AWS cloud services.
- Practical workshops and real case studies in various sectors (industry, trade, health).
- Feedback: Sharing best practices and common mistakes in business.
- Simulations and tools: Using simulators and AWS for interactive workshops.
Evaluation
- MCQ at the end of training.
- Practical case studies.
- Continuous evaluation with personalized feedback.
Normative References
- AWS Well-Architected Framework.
- GDPR (General Data Protection Regulation).
- CCPA (California Consumer Privacy Act).
- HIPAA (Health Insurance Portability and Accountability Act).
- ISO 27001, SOC 2 (Service Organization Control).
- PCI-DSS (Payment Card Industry Data Security Standard).
- NIST Cybersecurity Framework.