Data Architecture Fundamentals Training is a practical, foundational program designed to equip learners with essential skills in designing, structuring, and managing enterprise data systems. This training focuses on data architecture principles, data modeling, data lifecycle management, integration patterns, governance frameworks, and modern data platform design. Participants will gain real-world understanding of how data flows across systems and how scalable, secure, and high-performance data architectures are built for analytics, AI, and enterprise applications.

Participants will develop strong foundational expertise in data architecture, enabling them to design structured, scalable, and governed data systems aligned with enterprise and analytics requirements.

• Data Architects and Data Engineers
• Solution Architects and IT Architects
• Business Intelligence Professionals
• Software Developers working with data systems
• IT Professionals transitioning into data architecture roles

• Basic understanding of databases and data concepts
• Familiarity with IT systems and software applications
• Basic knowledge of SQL is helpful but not mandatory
• Analytical thinking and structured problem-solving skills

• Core data architecture principles and frameworks understanding
• Data modeling techniques (conceptual, logical, physical)
• Data integration and ETL/ELT architecture design
• Data governance and data lifecycle management
• Structured and unstructured data handling concepts
• Modern data platforms (cloud and hybrid architecture basics)
• Data security and compliance fundamentals

Upon completion of this training, participants will be able to understand and design foundational data architecture solutions for enterprise environments. They will be capable of structuring data systems, defining integration strategies, and supporting scalable data platforms for analytics and business applications.

Introduction to Data Architecture Principles
• What is data architecture and its importance
• Enterprise data architecture components
• Data lifecycle and data flow concepts
• Overview of modern data ecosystems

Data Modeling and Structure Design
• Conceptual, logical, and physical data models
• Entity relationship modeling basics
• Normalization and denormalization concepts
• Data modeling best practices
Data Integration and Platform Design
• ETL vs ELT architecture patterns
• Data pipeline and ingestion strategies
• Batch and real-time data processing overview
• Cloud-based data architecture fundamentals

Data Governance and Enterprise Architecture
• Data governance frameworks and policies
• Data quality and metadata management
• Security, compliance, and data privacy concepts
• Building scalable enterprise data platforms

• Data architecture principles and frameworks
• Data modeling techniques
• Data integration patterns (ETL/ELT)
• Data governance and lifecycle management
• Cloud and modern data platform concepts
• Data security and compliance fundamentals

• Case study-based data architecture design exercises
• Practical data modeling assignments
• Scenario-based integration design tasks
• Trainer-led evaluation of architecture frameworks

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training will receive an AcadNXT Certification in Data Architecture Fundamentals Training, validating their expertise in enterprise data design, data modeling, integration architecture, and modern data platform fundamentals.