Get AWS Certified Big Data 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 instills skills in the design, implementation and management of Big Data solutions on the AWS platform. It covers concepts and services related to the collection, storage, processing, analysis and visualization of large amounts of data, taking advantage of specialized AWS services for Big Data.
Objectives of training
At the end of this training, participants will be able to:
- Understanding AWS services for Big Data: Mastering AWS services such as Amazon S3, Redshift, EMR, Kinesis, Athena, Glue, and QuickSight.
- Designing efficient Big Data architectures: Learn how to design scalable and secure architectures for processing and analyzing large amounts of data in AWS.
- Collecting, processing and integrating massive data: Knowing how to collect and integrate data from various sources using services such as Kinesis and AWS Glue.
- Analyze and view bulky data: Using services like Amazon Athena, Redshift, and QuickSight to analyze data and get insights from it.
- Optimize performance and reduce costs: Learn how to optimize the performance of Big Data services while controlling the associated costs.
- Apply safety and compliance practices: Implement security controls to protect data and ensure compliance with regulatory standards.
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 to Big Data Services and Architecture Design
- Key services for Big Data on AWS: S3, Redshift, Kinesis, Athena, EMR, AWS Glue, QuickSight.
- Presentation of cases of use of services to manage massive data volumes.
- Big Data Architecture: Good practices for designing solutions.
- Practical workshop: Create Big Data architecture on S3 and configure an ETL process with AWS Glue.
- Massive data processing with EMR (Apache Spark, Hadoop) and Kinesis.
- Practical workshop: Create a real-time data processing pipeline with Kinesis.
- Data analysis with Amazon Athena and visualization with QuickSight.
- Practical workshop: Create interactive reports and visualizations in QuickSight using the results of Athena.
- Performance optimization and cost management: Optimization of queries in Redshift and Athena.
- Techniques to manage the costs of Big Data services on AWS.
- Practical workshop: Optimize Big Data solution in EMR and Redshift.
- Data security: Access controls and data security with IAM, KMS, and CloudTrail.
- Review of key concepts and preparation for the AWS Certified Big Data – Specialty exam.
- White exam to test knowledge and prepare for the certification exam.
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.