Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Training Redshift Expert - Master AWS Data Warehouses training are: Advanced SQL mastery, data warehousing experience (Snowflake or BigQuery), AWS basics (S3, EC2), ETL knowledge.. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Redshift Expert - Master AWS Data Warehouses training is available in in-person. The format can be adapted to your needs (inter, intra, custom).

Training Redshift Expert - Master AWS Data Wareh... | Learni

The story of Learni

Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.

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Methods, approaches, and teaching resources

The Training Redshift Expert - Master AWS Data Warehouses training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.

The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.

Teaching resources provided

To ensure the quality of the Training Redshift Expert - Master AWS Data Warehouses training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and teaching resources

For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Training Redshift Expert - Master AWS Data Warehouses training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training access terms and deadlines

Training objectives

Master Redshift's distributed architecture and scalability

Optimize cluster and complex query performance

Implement advanced ETL pipelines with AWS Glue and Redshift

Secure data via IAM, VPC, and advanced encryption

Configure monitoring and auto-scaling for production environments

Integrate Redshift with Spectrum and Federated Query

Deploy high availability and disaster recovery solutions

Training program

Module 1Redshift Architecture: clusters, nodes, and scalability (AWS Console, CLI tools)

Dive into Redshift's leaderless architecture, configure multi-node clusters via AWS Console and CLI, test data distribution with hands-on exercises on DC2 vs RA3, analyze real workloads for automatic scaling, produce an optimized production-ready cluster blueprint, while mastering costs through dynamic resizing.

Module 2Performance Optimization: advanced SQL queries and tuning (EXPLAIN, WLM)

Optimize queries with ANALYZE, VACUUM, and SORTKEYS on real TPC-DS cases, implement Workload Management to prioritize critical jobs, test compression and materialized views live, measure gains up to 10x via hands-on exercises, generate custom performance reports to boost your data pipelines.

Module 3Advanced ETL Pipelines: Glue, Airflow, and Spectrum integration (pipeline deliverables)

Build complex ETLs with AWS Glue and Redshift Spectrum to query S3 without loading, orchestrate via Apache Airflow on MWAA, process terabytes in real-time with exercises on real datasets, integrate Federated Query for hybrid RDS-Redshift, deploy a fully functional end-to-end pipeline with built-in monitoring.

Module 4Security, Monitoring, and HA: IAM, CloudWatch, Concurrency Scaling (production cases)

Strengthen security with fine-grained IAM, VPC endpoints, and KMS encryption on audit scenarios, configure CloudWatch alarms and auto-scaling for load spikes, simulate disaster recovery with cross-region snapshots, test concurrency scaling live, finalize with a capstone project deployed in prod-like environment, ready to scale infinitely.