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 Data Mesh Patterns - Implementing Decentralized Data Architectures training are: Knowledge of data architecture, data lakes, data engineering principles, and distributed data management. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Data Mesh Patterns - Implementing Decentralized Data Architectures training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Training Data Mesh Patterns - Implementing Decen... | 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 Data Mesh Patterns - Implementing Decentralized Data Architectures 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 Data Mesh Patterns - Implementing Decentralized Data Architectures 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 Data Mesh Patterns - Implementing Decentralized Data Architectures 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

Master Data Mesh patterns for professional data architectures

Develop skills in decentralizing data in enterprises

Implement autonomous data domains with certifying governance

Design optimized inter-domain data pipelines

Optimize data discovery and monetization via Data Mesh

Deploy Data Mesh patterns in real-world certifying contexts

Training program

Module 1Fundamentals of Data Mesh Patterns and Decentralized Principles

Introduction to the four pillars of Data Mesh. Analysis of autonomous data domain patterns. Practical implementation of data decentralization. Study of real business cases. Exercises on identifying data domains. Configuration of a first Data Mesh pattern. Ongoing project: modeling a data domain. Discussion on organizational challenges. Practical implementation with open-source tools. Evaluation of skills acquired at the end of the day.

Module 2Advanced Data Mesh Patterns for Pipelines and Governance

Exploration of inter-domain data pipeline patterns. Implementation of federated data governance. Professional exercises on data product APIs. Real cases of self-service data platforms. Development of a decentralized data catalog. Integration of semantic federation patterns. Ongoing project: connecting data domains. Optimization of real-time data flows. Analysis of common business errors. Practice with Kubernetes and Kafka for Data Mesh.

Module 3Implementation and Deployment of Data Mesh Patterns in Production

Deployment of Data Mesh patterns in production environments. Practical implementation of data product monetization. Exercises on automated data discovery. Case studies of leading companies in Data Mesh. Finalization of the ongoing project with presentation. Optimization of performance and scalability. Governance, observability, and security. Skills evaluation via multiple-choice quiz. Perspectives on advanced Data Mesh evolution. Delivery of certifying course materials.

Evaluation method

Multiple-choice quiz to validate learning on Data Mesh Patterns at the end of the training
Continuous evaluation through practical exercises and business cases
Presentation of the ongoing Data Mesh project to the expert trainer