Enterprise Data Architecture Foundation equips data professionals with the foundational knowledge and practical skills needed to design modern enterprise data ecosystems. As organizations lean more on data-driven insights and AI, robust data architecture becomes critical for platforms that are scalable, secure, and efficient.
Data is a foundational enterprise asset, driving analytics, automation, and AI initiatives across industries. However, many organizations struggle with fragmented data landscapes, technical debt, and governance challenges that limit how effectively they can use their data. This course tackles those challenges with a structured approach to designing and implementing data architectures that support diverse workloads and evolving business needs.
Participants explore architectural frameworks, data platform components, cloud-native infrastructure, and best practices for building scalable, secure data ecosystems. Through guided labs and design exercises, learners build architectural skills that support analytics, operational workloads, and emerging AI and ML initiatives. Day one focuses on foundational concepts and platform design, while day two emphasizes governance, security, operationalization, and strategic planning.
Hands-on labs anchor each module, starting with an Assessing Enterprise Data Architecture Needs exercise. Labs then move through Designing a Data Platform Reference Architecture and a dedicated Data Modeling Exercise. Attendees also work through a Designing a Hybrid Data Platform lab, applying cloud and multi-cloud patterns to a realistic scenario. Day two labs shift toward governance and operations, including Designing a Data Governance Framework and Designing Secure Data Access Controls. They also include a Data Pipeline Observability Exercise. The course concludes with an Enterprise Data Architecture Capstone Design lab. There, participants apply what they’ve learned to a complete architecture of their own design.
Who Should Attend
Data Architects, Ops & Engineers, Cloud Engineers, Analytics Engineers, Technical Managers
What Attendees Will Learn
Upon completing Enterprise Data Architecture Foundation, participants will be able to:
- Understand the principles and scope of enterprise data architecture
- Design modern data platforms supporting analytics, operational, and AI workloads
- Apply data governance, security, and compliance frameworks effectively
- Architect scalable data pipelines and storage solutions
- Integrate cloud-native and hybrid data infrastructure
- Enable data discoverability, quality, and lifecycle management
- Align data architecture strategies with business and operational goals
Prerequisites
Participants should have:
- Basic understanding of databases, analytics, or data engineering concepts
- Familiarity with cloud or distributed systems helpful
- General DevOps or platform engineering exposure beneficial
- No prior enterprise data architecture experience required