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 Quality - Garantir la fiabilité des données d'entreprise training are: Expérience en SQL avancé, ETL, Python pour data processing et bases de data quality. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Formation Data Quality - Garantir la fiabilité des données d'entreprise training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Formation Data Quality - Garantir la fiabilité d... | 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 Quality - Garantir la fiabilité des données d'entreprise 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 Quality - Garantir la fiabilité des données d'entreprise 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 Quality - Garantir la fiabilité des données d'entreprise 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 techniques avancées de profilage et nettoyage Data Quality pour projets professionnels

Développer des pipelines automatisés de validation de données en entreprise

Implémenter un monitoring en temps réel des métriques Data Quality certifiantes

Concevoir des règles de gouvernance adaptées aux compétences data stratégiques

Optimiser la qualité des données avec outils cloud et open-source

Déployer des solutions Data Quality scalables pour l'analyse prédictive

Training program

Module 1Diagnostic Data Quality : évaluer la maturité des données (profilling, audits, benchmarks outils)

Immersion immédiate dans l'audit complet de vos datasets via outils comme Great Expectations et Talend Data Catalog, profilage automatisé pour détecter duplicatas, incohérences et anomalies statistiques, exercices pratiques sur cas réels d'entreprise avec calcul de scores DQ, élaboration d'un rapport diagnostic actionable et plan de remédiation priorisé, tout en intégrant des benchmarks sectoriels pour mesurer l'impact business immédiat.

Module 2Pipelines Data Quality : automatiser nettoyage et validation (ETL avancés, règles métier)

Conception et implémentation de pipelines robustes avec Apache Airflow et dbt pour nettoyage automatisé, définition de règles de validation complexes basées sur schémas JSON et regex avancées, tests unitaires sur flux de données massives, simulation d'erreurs réelles pour renforcer la résilience, production de dashboards interactifs avec Tableau Prep pour visualiser la conformité, et génération de livrables prêts pour production en entreprise certifiante.

Module 3Gouvernance Data Quality : monitoring et optimisation (cloud, ML, métriques KPI)

Déploiement de systèmes de monitoring temps réel via AWS Glue et Databricks avec alertes proactives sur dérives DQ, intégration de ML pour détection d'anomalies prédictives sur datasets volumineux, optimisation des performances avec partitioning et indexing intelligents, cas d'étude sur gouvernance multi-sources pour IA fiable, élaboration de KPI Data Quality alignés sur objectifs business, et finalisation d'un framework scalable avec documentation complète pour déploiement en production professionnelle.