AWS Certified Data Analytics
Get AWS Data Analytics certifcation
and boost your career
Eligible for CPF and multiple funding options up to 100%
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3P Approach
Our training center guides you in identifying the ideal course and helps you maximize funding opportunities.
We give you everything you need to start with confidence.
Experience an immersive, intensive program with hands-on workshops and real-world case studies.
Learn by doing and build practical skills you can apply directly to future projects.
At the end of your journey, we assess your skills, issue a certificate, and support you to ensure success in your professional projects.
You are now ready to excel!
Course Description
This course enables participants to architect cloud data management solutions using Amazon Web Services database services such as Amazon RDS, DynamoDB, or Aurora, while taking into account performance, scalability, availability, security, and cost requirements.
Learning Objectives
By the end of this course, participants will be able to:
- Master AWS services for Big Data: Amazon S3, Redshift, AWS Glue, Kinesis, Athena, QuickSight.
- Design scalable analytics 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 course for?
The course is intended for a wide audience, including:
- Cloud solution architects specializing in the design of Big Data and analytics solutions on AWS.
- Data engineers responsible for processing and integrating data in AWS environments.
- Data analysts working with massive datasets and extracting insights using AWS services.
- Developers and Big Data engineers using services such as Redshift, EMR, Kinesis, Athena, QuickSight.
- Data leaders such as Chief Data Officers (CDOs) responsible for data analysis within the company.
- Consultants and cloud professionals who help companies migrate to or design analytics solutions on AWS.
Prerequisites
No specific prerequisites are required. This course is accessible to anyone wishing to discover AWS, though basic knowledge of IT or information systems can be an asset.
Course Outline
Introduction to AWS Big Data services and analytics solution design
- Overview of AWS Big Data services: S3, Redshift, Kinesis, AWS Glue, Athena, QuickSight.
- Architecture of data solutions and large-scale analytics in AWS.
- Design of storage (S3), processing (EMR, Glue), and analytics (Athena, Redshift) architectures.
- Hands-on workshop: Design a data processing architecture with S3 and Glue.
- Data processing and transformation with AWS Glue and Kinesis.
- Hands-on workshop: Create an ETL pipeline with AWS Glue to clean and load data into Redshift.
- Data analysis with Amazon Athena and visualization with QuickSight.
- Hands-on workshop: Create interactive dashboards in QuickSight and analyze data in Athena.
- Performance optimization and cost management: Optimize SQL queries in Redshift and Athena, reduce costs with S3, EMR, Redshift.
- Hands-on workshop: Optimize a data processing solution in EMR.
- Data security and preparation for the AWS Certified Data Analytics – Specialty exam: Review key concepts and take a mock exam to test knowledge.
Course Highlights
- Teaching approach: Alternating theory and practice for better assimilation of concepts.
- Qualified instructors: Trainers specialized with real-world experience in the Cloud domain.
- Tools and learning materials: Access to online resources, live demonstrations, and real case studies.
- Accessibility: Course open to all, with no advanced technical prerequisites.
Teaching Methods and Tools Used
- Live demonstrations with AWS cloud services.
- Hands-on workshops and real case studies in various sectors (industry, retail, healthcare).
- Experience feedback: Sharing best practices and common mistakes in companies.
- Simulations and tools: Use of simulators and AWS for interactive workshops.
Assessment
- End-of-course multiple-choice quiz.
- Practical case studies.
- Continuous assessment 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.
Modalities
In-house
The duration and program can be customized according to the specific needs of your company
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