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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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Don't let this gap widen
Without advanced mastery of Amazon Redshift optimization, enterprises suffer from inefficient cloud data warehouses plagued by slow queries and ballooning costs.
AWS reports that poorly tuned clusters waste up to $300,000 annually per organization in excess compute and storage fees, with 60% of query failures linked to suboptimal configurations.
This drags down BI insights, exposes teams to 35% higher downtime risks, and jeopardizes career advancement amid rising demands for agile analytics.
Every month without these skills, companies forfeit millions in untapped revenue opportunities.
The Training Amazon Redshift - Optimizing Cloud 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.
To ensure the quality of the Training Amazon Redshift - Optimizing Cloud Data Warehouses training, Learni provides the following 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.
The assessment of skills acquired during the Training Amazon Redshift - Optimizing Cloud Data Warehouses training is carried out through:
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.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Configuration of multi-node Redshift clusters. Analysis of DC2 and RA3 node types. Management of slices and distribution keys. Hands-on practice on real enterprise cases. Exercises on compression and sorting. Ongoing project: modeling a data warehouse. Initial performance optimization. Integration with S3 for staging. Load testing on massive datasets. Best practices for high availability. Troubleshooting common issues. AWS development environment preparation. Setting up secure IAM roles. Architecture validation for production.
Analysis of SQL query execution plans. Use of EXPLAIN and SVG. Optimization of joins and aggregations. Management of workloads and concurrency scaling. Hands-on with professional exercises. Ongoing project: tuning slow queries. Configuration of advanced Materialized Views. Monitoring with CloudWatch and system tables. Auto-scaling and live cluster resize. Benchmarks on real datasets. Cost reduction via pause/resume. Real enterprise cases: BI optimization. Automated vacuum and analyze techniques. WLM query queue management.
Redshift Spectrum integration for external S3 queries. ETL pipeline development with AWS Glue and Lambda. Massive loading via COPY and UNLOAD. Hands-on with heterogeneous data flows. Ongoing project: ingesting external datasets. Federated Query to Aurora and RDS. Advanced SQL transformations and UDFs. Securing with VPC and KMS encryption. Exercises on enterprise Big Data cases. Orchestration with Step Functions. Dynamic partition management. Performance tuning for large-scale ETL. Real-time ETL job monitoring. Best practices for data lakes.
IAM, AQUA, and zero-ETL configuration. Advanced monitoring with Performance Insights. CloudWatch alerts and logs. Hands-on production deployment. Ongoing project: finalization and defense. Cross-region backup and restore. GDPR compliance and audit trails. Integration with BI tools like Tableau and QuickSight. Scalability for petabytes. Advanced incident resolution. Cost optimization with reserved instances. Legacy migration to Redshift. DevOps best practices with Terraform. Skills evaluation via quiz. Delivery of certifying materials.
Target audience
Data engineers, Big Data architects, and BI analysts seeking to advance their Redshift skills in an enterprise environment
Prerequisites
Advanced SQL proficiency, AWS basics (S3, EC2), experience in data warehousing and ETL
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