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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.
10 spots per session maximum — 7 already taken
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30 free minutes with a training advisor — no commitment.
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Don't let this gap widen
Without advanced mastery of Amazon Redshift, data teams grapple with chronic query inefficiencies and scaling failures, wasting 30-50% more compute resources monthly.
In fact, 65% of cloud data warehouse outages stem from mismanagement, incurring average costs of $250,000 per incident in downtime, recovery, and lost analytics insights.
Enterprises face regulatory non-compliance risks, eroded competitive edges, and stalled big data projects, threatening executive careers and multimillion-dollar revenue streams.
Every quarter without these skills, businesses amplify vulnerabilities in their cloud data infrastructure.
The Training: Mastering Amazon Redshift: Managing the Cloud Data Warehouse for Big Data Analysis 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: Mastering Amazon Redshift: Managing the Cloud Data Warehouse for Big Data Analysis 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: Mastering Amazon Redshift: Managing the Cloud Data Warehouse for Big Data Analysis 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.
Overview of AWS data services, cloud data warehouse concepts, introduction to Redshift and use cases. Creating and configuring a Redshift cluster, star schema and data distribution, initial data loading (COPY, UNLOAD, S3 management). Practice: Deploying a first data warehouse and loading massive datasets.
Writing performant queries, joins, and analytic functions. Introduction to Redshift Spectrum: analyzing external data (Parquet, JSON, CSV) stored on S3 within the same warehouse. Optimizations: sorting, distribution, vacuum management, monitoring with CloudWatch, query logs. Introduction to security: VPC, IAM, roles, encryption. Integration with AWS Glue, Lambda, and ETL process automation.
Fine-grained access management, roles, federated authentication, and advanced security: auditing, logging, column-level access control. Connecting to BI tools: demonstrations with Tableau, QuickSight, Power BI, and automated report extraction. Implementing automated maintenance, archiving, and backup/restore jobs. Complete case study: industrializing a data pipeline on Redshift, migration scenarios from traditional data warehouses.
Target audience
Data engineers, database administrators, BI analysts, IT project managers, cloud architects, and anyone involved in managing and analyzing large-scale data in enterprise settings.
Prerequisites
Mastery of relational concepts, basic SQL knowledge, and fundamental cloud architecture principles recommended.
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