Data Lakehouse Architecture: Implementing Delta Lake and Apache Iceberg for Production Systems

About the Course

This professional training course explores the critical role of modern data lakehouse architecture in enterprise data platforms. Organizations are increasingly adopting lakehouse architectures that combine data lake flexibility with data warehouse reliability, enabling unified analytics and operational intelligence across the organization.

This course provides hands-on experience implementing two leading open-table format technologies: Delta Lake and Apache Iceberg. You'll learn how to architect robust production systems that handle real-world complexity, ensure data quality, and support complex analytical queries at scale.

Course Objectives

• Understand lakehouse architecture principles and how they differ from traditional data warehouses and data lakes
• Implement Delta Lake with ACID transactions, time-travel capabilities, and schema evolution in production environments
• Deploy Apache Iceberg for handling complex analytics workloads with schema versioning and hidden partitioning
• Design data governance frameworks, security models, and access control mechanisms
• Optimize performance through partitioning strategies, indexing, and query optimization techniques
• Build real-world solutions for handling streaming data, incremental processing, and upsert operations
• Implement monitoring, debugging, and maintenance strategies for production lakehouse systems

Target Audience

• Data engineers and architects designing next-generation data platforms
• Solutions architects implementing enterprise data solutions
• Technical leaders responsible for data infrastructure decisions
• Database administrators transitioning to cloud-native environments
• Analytics engineers building production analytical systems

What You Will Benefit as a Learner

• Practical Implementation Skills: Build production-ready lakehouse systems using Delta Lake and Apache Iceberg with real-world code examples and patterns
• Architecture Expertise: Design scalable, maintainable data platforms that balance performance, cost, and reliability requirements
• Production Operations Knowledge: Master monitoring, troubleshooting, and optimization techniques for managing lakehouse systems at scale
• Strategic Understanding: Make informed technology choices between Delta Lake, Iceberg, and other approaches for specific use cases
• Data Quality & Governance: Implement frameworks ensuring data accuracy, lineage tracking, and compliance across the organization

Training Methodology

• Interactive Labs: Hands-on exercises using cloud environments (AWS, Azure, GCP) with pre-configured datasets and real-world scenarios
• Case Studies: Analyze industry implementations and discuss architectural trade-offs through guided group discussions
• Live Coding: Instructor-led demonstrations of Delta Lake and Iceberg implementations with detailed code walkthroughs
• Architecture Workshops: Collaborative design sessions where participants architect solutions for complex business requirements
• Q&A and Mentoring: Expert instructors available for technical questions and guidance on applying concepts to your environment