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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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Allan BusiDec 1, 20269 min readOklahoma CityThe Training Data Mesh Patterns - Mastering 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.
To ensure the quality of the Training Data Mesh Patterns - Mastering Decentralized Data Architectures 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 Data Mesh Patterns - Mastering Decentralized Data Architectures 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.
Dive into the principles of Data Mesh patterns to identify and delineate your business data domains, using Domain-Driven Design to map autonomous boundaries, model your first data products with tools like Collibra or DataHub for metadata, conduct practical workshops to decompose an existing data lake into federated domains, produce a domain map with maturity metrics, and validate through real business cases for effective decentralized governance from day one.
Apply Data Mesh interoperability patterns by designing standardized data contracts between domains, integrate Apache Kafka for cross-domain event streams and dbt for reliable transformations, develop autonomous data pipelines via hands-on exercises on a simulated enterprise red thread project, test resilience with failure scenarios, generate secure federated data APIs, and optimize performance for proven scalability, transforming silos into a collaborative and performant data ecosystem.
Finalize your architecture by deploying federated governance with self-imposed standards, use Prometheus and Grafana for data product observability, implement data CI/CD via GitHub Actions and ArgoCD adapted for Data Mesh, monetize data through internal catalogs with tools like Amundsen, perform a complete production rollout of your red thread project with business metrics, assess ROI impact via concrete KPIs, and leave with an enterprise adoption plan to accelerate data value in production.
10 participants max.
$4,410 / per person
3 days
distancielTarget audience
Data engineers, data architects, data managers and CTOs seeking to upskill on Data Mesh
Prerequisites
Advanced data engineering experience, mastery of data lakes and warehouses, knowledge of domain-driven design
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Avancée
€2,100.002 journées
distanciel10 pers. max.Expert€2,100.002 journéesdistanciel10 pers. max.Expert€1,050.001 journéedistanciel10 pers. max.Intermédiaire€1,050.001 journéedistanciel10 pers. max.