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 Formation Data Lake 2026 - Architectures data scalables training are: Connaissances en SQL avancé, Python pour data et bases en cloud storage comme S3 ou ADLS. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Formation Data Lake 2026 - Architectures data scalables training is available in présentiel. The format can be adapted to your needs (inter, intra, custom).

Formation Data Lake 2026 - Architectures data sc... | 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 Formation Data Lake 2026 - Architectures data scalables 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 Formation Data Lake 2026 - Architectures data scalables 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 Formation Data Lake 2026 - Architectures data scalables 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 objectives

Maîtriser les architectures Data Lake 2026 pour des projets professionnels scalables

Développer des compétences en ingestion et stockage massif de données structurées/non structurées

Implémenter des formats open table comme Iceberg et Delta Lake en entreprise

Concevoir la gouvernance data certifiante pour conformité RGPD et sécurité

Optimiser les pipelines Data Lake avec Spark et outils cloud pour performances maximales

Déployer des Data Lakes interconnectés à des analytics et ML en production

Intégrer des pratiques DevDataOps pour une maintenance efficace en équipe

Training program

Module 1Architecture : concevoir un Data Lake 2026 scalable (Iceberg, Delta Lake, S3/ADLS)

Plongez dans les fondements des Data Lakes modernes 2026 en analysant les besoins métier de votre entreprise, configurez un environnement cloud avec AWS S3 ou Azure Data Lake Storage, implémentez des schémas évolutifs via Apache Iceberg pour gérer pétaoctets de données brutes, réalisez des exercices pratiques d'ingestion batch et streaming avec Kafka, produisez votre premier blueprint architectural documenté et testé pour un cas concret d'analyse prédictive.

Module 2Implémentation : pipelines Data Lake 2026 performants (Spark, Databricks, gouvernance)

Construisez des pipelines robustes pour votre Data Lake 2026 en utilisant Apache Spark sur Databricks, intégrez Delta Lake pour ACID transactions et time travel sur données massives, développez des ETL automatisés traitant JSON, Parquet et Avro, appliquez des règles de gouvernance avec Collibra ou Atlas pour tagging et lignage, testez en conditions réelles avec volumes simulés d'entreprise, générez des rapports de performance et un plan de monitoring opérationnel prêt à déployer.

Module 3Optimisation : Data Lake 2026 en production (query federation, ML integration, DevDataOps)

Optimisez votre Data Lake 2026 pour l'exploitation en continu via federation de queries avec Trino ou Presto, intégrez des workflows ML avec MLflow directement sur le lac, déployez CI/CD DevDataOps avec GitHub Actions et Terraform pour scalabilité infinie, analysez des métriques de coût et performance sur cas d'usage e-commerce réels, résolvez des pièges courants comme data skew, finalisez un livrable complet : dashboard gouvernance et stratégie d'évolution 2026 pour votre organisation.