Data Mesh Architecture Training Course: Decentralize Your Data

Introduction

Transform your data strategy with our Data Mesh Architecture Training Course. This program is designed to equip you with the essential skills to implement a decentralized data architecture, enabling you to build scalable, agile, and domain-oriented data platforms. In today's data-driven world, mastering data mesh architecture is crucial for organizations seeking to break down data silos and empower domain teams. Our data mesh architecture training course offers hands-on experience and expert guidance, empowering you to design and implement a modern data infrastructure.

This decentralize your data training delves into the core concepts of data mesh, covering topics such as domain-driven data ownership, data as a product, and self-serve data infrastructure. You'll gain expertise in using industry-standard techniques to implement a decentralized data architecture, meeting the demands of modern data-intensive organizations. Whether you're a data architect, data engineer, or data strategist, this Data Mesh Architecture course will empower you to build and manage a distributed and efficient data ecosystem.

Target Audience:

• Data Architects
• Data Engineers
• Data Strategists
• Data Product Managers
• Cloud Architects
• Business Intelligence Developers
• Anyone needing data mesh architecture skills

Course Objectives:

• Understand the fundamentals of data mesh architecture.
• Master domain-driven data ownership and data as a product.
• Utilize self-serve data infrastructure platforms.
• Implement federated computational governance.
• Design and build distributed data products.
• Optimize data mesh for scalability and interoperability.
• Troubleshoot and address common challenges in data mesh implementation.
• Implement data governance and security in a decentralized environment.
• Integrate data mesh with various data sources and analytics tools.
• Understand how to handle data discovery and metadata management in a mesh.
• Explore advanced data mesh patterns (e.g., data contracts, data APIs).
• Apply real world use cases for data mesh architecture.
• Leverage data mesh tools and frameworks for efficient implementation.

Duration

10 Days

Course content

Module 1: Introduction to Data Mesh Architecture

• Fundamentals of data mesh architecture.
• Overview of domain-driven ownership, data as a product, and federated governance.
• Setting up a data mesh development environment.
• Introduction to data mesh principles and components.
• Best practices for data mesh implementation.

Module 2: Domain-Driven Data Ownership

• Mastering domain-driven data ownership and data as a product.
• Utilizing domain-driven design principles for data management.
• Implementing data ownership models.
• Designing and building domain-oriented data products.
• Best practices for data ownership.

Module 3: Self-Serve Data Infrastructure

• Utilizing self-serve data infrastructure platforms.
• Implementing data infrastructure automation.
• Designing and building self-serve data tools.
• Optimizing infrastructure for data product development.
• Best practices for self-serve infrastructure.

Module 4: Federated Computational Governance

• Implementing federated computational governance.
• Utilizing policies and standards for data interoperability.
• Designing and building governance frameworks.
• Optimizing governance for decentralized data management.
• Best practices for governance.

Module 5: Distributed Data Products

• Designing and building distributed data products.
• Utilizing data APIs and data contracts.
• Implementing data product development workflows.
• Optimizing data products for consumption.
• Best practices for data products.

Module 6: Scalability and Interoperability

• Optimizing data mesh for scalability and interoperability.
• Utilizing data virtualization and federation techniques.
• Implementing data standardization and harmonization.
• Designing scalable data mesh architectures.
• Best practices for scalability.

Module 7: Troubleshooting Data Mesh Implementation

• Troubleshooting and addressing common challenges in data mesh implementation.
• Analyzing data product integration issues.
• Utilizing problem-solving techniques for resolution.
• Resolving common data mesh errors.
• Best practices for troubleshooting.

Module 8: Data Governance and Security

• Implementing data governance and security in a decentralized environment.
• Utilizing data access control and security policies.
• Designing and building data governance models.
• Optimizing security for distributed data.
• Best practices for governance.

Module 9: Integration with Data Tools

• Integrating data mesh with various data sources and analytics tools.
• Utilizing data integration platforms and APIs.
• Implementing data mesh with cloud-native data platforms.
• Optimizing integration for data consumption.
• Best practices for integration.

Module 10: Data Discovery and Metadata Management

• Understanding how to handle data discovery and metadata management in a mesh.
• Utilizing data catalogs and metadata repositories.
• Implementing data lineage tracking.
• Designing efficient metadata management strategies.
• Best practices for metadata.

Module 11: Advanced Data Mesh Patterns

• Exploring advanced data mesh patterns (data contracts, data APIs).
• Utilizing data contracts for data product interoperability.
• Implementing data APIs for data access.
• Designing and building advanced data mesh solutions.
• Optimizing advanced techniques for specific applications.
• Best practices for advanced patterns.

Module 12: Real-World Use Cases

• Implementing data mesh for enterprise-wide data management.
• Utilizing data mesh for real-time data analytics.
• Implementing data mesh for data-driven product development.
• Utilizing data mesh for data democratization.
• Best practices for real-world applications.

Module 13: Data Mesh Tools Implementation

• Utilizing data mesh tools and frameworks (DataHub, Amundsen).
• Implementing data mesh with specific tools.
• Designing and building automated data mesh workflows.
• Optimizing tool usage for efficient development.
• Best practices for tool implementation.

Module 14: Data Product Monitoring

• Implementing data product monitoring.
• Utilizing data product metrics and logs.
• Designing and building performance dashboards.
• Optimizing monitoring for data product health.
• Best practices for monitoring.

Module 15: Future Trends in Data Mesh

• Emerging trends in data mesh architecture.
• Utilizing AI for data product automation.
• Implementing data mesh in cloud-native environments.
• Best practices for future applications.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.