Welcome to the Data Mesh Architectures and Implementations course, where you'll begin a journey to acquire practical expertise in designing and deploying decentralized, domain-driven data systems. Harness the power of Data Mesh principles to transform how your organization owns, governs, and delivers data.
By the end of this course, you'll be able to:
- Design domain-oriented Data Mesh architectures that establish clear ownership boundaries, data product structures, and self-serve platform capabilities.
- Implement federated computational governance by applying scalable policies, data quality guardrails, and compliance controls across distributed domain teams.
- Build decentralized data pipelines and storage solutions using domain-owned ETL patterns, API-based data exchange, and service mesh models for enterprise reliability.
- Integrate Generative AI into Data Mesh environments to deploy intelligent, LLM-powered data pipelines and AI-augmented workflows across domain-owned platforms.
This course is designed for a diverse audience: data engineers, data architects, analytics engineers, and senior data professionals who are looking to build scalable, domain-driven data systems and lead modern enterprise data transformation initiatives.
Prior experience with data engineering concepts such as data pipelines, cloud storage, or distributed systems is beneficial when working with Data Mesh architectures.
Embark on an architectural journey to master Data Mesh and build the skills needed to design intelligent, governed, and production-ready data platforms for the modern enterprise.
Establish a strong architectural foundation by understanding Data Mesh as a decentralized data paradigm. Design domain-oriented ownership models that clearly define accountability and data boundaries. Apply product-thinking principles to structure data as discoverable, reliable, and interoperable data products. An architect self-serve platform capabilities that empower domain teams while enforcing federated computational governance through scalable policies and guardrails.
Das ist alles enthalten
15 Videos7 Lektüren5 Aufgaben
Infos zu Modulinhalt anzeigen
15 Videos•Insgesamt 85 Minuten
Course Introduction•4 Minuten
Introduction to Data Mesh•6 Minuten
Data Mesh Architecture and Tools•6 Minuten
Teams and Ownership in a Data Mesh Organization•6 Minuten
Evolution of Modern Data Architecture•5 Minuten
Domain-Oriented Data Ownership in Data Mesh•5 Minuten
Federated Governance Models and Guardrails•10 Minuten
Module Summary: Foundations of Data Mesh Architecture•10 Minuten
5 Aufgaben•Insgesamt 39 Minuten
Knowledge Check: Data Mesh Architecture and Core Principles Assessment•15 Minuten
Practice Assignment: Data Mesh Architecture and Organizational Concepts•6 Minuten
Practice Assignment: Mapping Domains to Data Ownership•6 Minuten
Practice Assignment: Defining Platform Capabilities for Domain Teams•6 Minuten
Practice Assignment: Designing Governance Rules for Data Products•6 Minuten
Integrating GenAI with Data Mesh
Modul 2•2 Stunden abzuschließen
Moduldetails
Design AI-ready data ecosystems by aligning GenAI capabilities with decentralized data products. Integrate GenAI into domain-owned architectures using scalable integration patterns and platform services. Engineer intelligent data discovery and analytics workflows powered by GenAI. Evaluate business impact, governance considerations, and architectural trade-offs when embedding AI into distributed data environments.
Das ist alles enthalten
11 Videos4 Lektüren4 Aufgaben
Infos zu Modulinhalt anzeigen
11 Videos•Insgesamt 64 Minuten
Introduction to GenAI for Modern Data Platforms•6 Minuten
Data Readiness for GenAI in a Data Mesh•6 Minuten
Demonstration: Identifying AI-Ready Data Products in a Data Mesh•7 Minuten
Transforming Data Mesh with GenAI•5 Minuten
Demonstration: Integrating a GenAI Service with a Domain Data Product•6 Minuten
Demonstration: GenAI-Powered Support Operations Analytics•3 Minuten
Demonstration: Connecting GenAI to a Self-Serve Data Platform•6 Minuten
Business Impact of GenAI in a Data Mesh Architecture•6 Minuten
Demonstration: Data Discovery and Insights Before vs. After GenAI Integration•7 Minuten
Demonstration: Designing a GenAI-Powered Data Discovery Flow•7 Minuten
Demonstration: Building a Retrieval-Based RAG System•5 Minuten
4 Lektüren•Insgesamt 40 Minuten
AI Capabilities Mapped to Data Mesh Components•10 Minuten
Integration Patterns for GenAI in Data Mesh•10 Minuten
Measuring Improvements from GenAI-Enabled Data Mesh•10 Minuten
Module Summary: Integrating GenAI with Data Mesh•10 Minuten
4 Aufgaben•Insgesamt 33 Minuten
Knowledge Check: GenAI Integration with Data Mesh•15 Minuten
Practice Assignment: GenAI Concepts and AI Tooling in Data Mesh•6 Minuten
Practice Assignment: GenAI Integration Patterns and Architecture Decisions•6 Minuten
Practice Assignment: GenAI Use Case Analysis and Impact Evaluation•6 Minuten
Enterprise-Grade Storage, Pipelines, and Data Exchange
Modul 3•3 Stunden abzuschließen
Moduldetails
Architect scalable domain-owned storage solutions and decentralized ETL pipelines. Manage cross-domain dependencies while preserving autonomy and reducing coupling. Implement secure data exchange using APIs and service mesh patterns. Apply data quality monitoring, observability, and governance controls to stabilize distributed systems and ensure enterprise-grade reliability.
Das ist alles enthalten
15 Videos5 Lektüren5 Aufgaben
Infos zu Modulinhalt anzeigen
15 Videos•Insgesamt 85 Minuten
Domain-Owned Data Storage in a Data Mesh•5 Minuten
Demonstration: Mapping Domain Data Products to Storage Solutions•6 Minuten
Demonstration: Centralized vs. Domain-Owned Storage Models•5 Minuten
Domain-Oriented Data Pipelines for Data Mesh•5 Minuten
Demonstration: Designing a Domain-Owned ETL Pipeline•7 Minuten
Demonstration: Managing Cross-Domain Data Dependencies•7 Minuten
Demonstration: Connecting BI Tools to Domain Data Products•5 Minuten
Exchanging Data Products Using APIs and Service Mesh•5 Minuten
Demonstration: Designing APIs for Data Product Access•6 Minuten
Demonstration: Service Mesh Patterns for Secure Data Exchange•6 Minuten
Data Consumption and Reporting in a Data Mesh•6 Minuten
Managing and Monitoring Data Quality in a Decentralized System•5 Minuten
Demonstration: Data Quality Monitoring Dashboard and Feedback Loop•7 Minuten
5 Lektüren•Insgesamt 50 Minuten
Domain-Owned Storage Patterns and Design Considerations•10 Minuten
Designing and Operating Domain-Oriented Data Pipelines•10 Minuten
Security and Compliance Patterns for Data Mesh•10 Minuten
Data Consumption, Quality Metrics, and Monitoring Framework•10 Minuten
Module Summary: Enterprise-Grade Storage, Pipelines, and Data Exchange•10 Minuten
5 Aufgaben•Insgesamt 39 Minuten
Knowledge Check: Data Mesh Implementation Assessment•15 Minuten
Practice Assignment: Evaluating Storage Models for Domain Data Products•6 Minuten
Practice Assignment: Modeling Decentralized ETL Pipelines and Dependencies•6 Minuten
Practice Assignment: Design Secure Data Access Rules•6 Minuten
Practice Assignment: Data Consumption, Quality, and Monitoring Concepts•6 Minuten
Course Wrap-Up and Assessment
Modul 4•2 Stunden abzuschließen
Moduldetails
Design an end-to-end GenAI-enabled data mesh architecture aligned with business objectives. Evaluate maturity, scalability, and governance readiness across domains. Deliver a comprehensive architecture blueprint that balances autonomy, standardization, innovation, and control.
Das ist alles enthalten
1 Video1 Lektüre2 Aufgaben1 Diskussionsthema
Infos zu Modulinhalt anzeigen
1 Video•Insgesamt 4 Minuten
Course Summary: Data Mesh Architecture and Implementations•4 Minuten
1 Lektüre•Insgesamt 30 Minuten
Practice Project: GenAI-Enabled Data Mesh Architecture for Enterprise Transformation•30 Minuten
2 Aufgaben•Insgesamt 60 Minuten
End Course Knowledge Check: Data Mesh Architecture and Implementations•30 Minuten
Intelligent Enterprise Mesh: Building a GenAI-Enabled Data Mesh Architecture•30 Minuten
1 Diskussionsthema•Insgesamt 5 Minuten
Driving Organizational Transformation with Data Mesh•5 Minuten
Edureka is an online education platform focused on delivering high-quality learning to working professionals. We have the
highest course completion rate in the industry and we strive to create an online ecosystem for our global learners to equip
themselves with industry-relevant skills in today’s cutting edge technologies.
Data Mesh is a decentralized data architecture that treats data as a domain-owned product governed by federated policies, replacing bottleneck-prone centralized data lakes.
Who should take this Data Mesh course?
This course is ideal for data engineers, data architects, analytics engineers, and data platform leads looking to build scalable, domain-driven enterprise data systems.
What hands-on skills will I gain?
You'll design domain-owned data products, build decentralized ETL pipelines, implement federated governance, and integrate GenAI into Data Mesh platforms using Databricks.
Does this course cover GenAI and Data Mesh integration?
Yes. A dedicated module covers LLM-powered data products, RAG pipeline design, and AI-augmented governance within a Data Mesh architecture.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Finanzielle Unterstützung verfügbar, weitere Informationen
¹ Einige Aufgaben in diesem Kurs werden mit AI bewertet. Für diese Aufgaben werden Ihre Daten in Übereinstimmung mit Datenschutzhinweis von Courseraverwendet.