This training focuses on Apache Iceberg architecture, table design, schema evolution, partitioning strategies, time travel, data versioning, and integration with big data engines such as Spark, Hive, and Flink.
Overview
Apache Iceberg Training is a practical, hands-on program designed to equip learners with the skills required to work with modern open table formats for large-scale data lakes. This training focuses on Apache Iceberg architecture, table design, schema evolution, partitioning strategies, time travel, data versioning, and integration with big data engines such as Spark, Hive, and Flink. Participants will gain real-world experience in building reliable, scalable, and high-performance data lakehouse solutions for analytics and data engineering workloads.
Learning Outcomes
Participants will gain strong practical expertise in Apache Iceberg, enabling them to design modern data lake architectures, manage evolving datasets, and optimize large-scale analytics workloads.
Duration & Delivery Mode
17 hours
Target Audience
• Data Engineers and Analytics Engineers
• Big Data Developers and Architects
• Data Platform and Lakehouse Engineers
• BI Professionals working with large datasets
• IT Professionals transitioning into modern data lake architectures
Pre-requisites
• Basic understanding of SQL and data warehousing concepts
• Familiarity with Apache Spark or Hadoop ecosystem basics is helpful
• Understanding of data processing and ETL concepts
• Basic knowledge of distributed systems
Skillset Achieved
• Apache Iceberg architecture and table format understanding
• Data lakehouse design principles
• Schema evolution and metadata management
• Partitioning and query optimization strategies
• Time travel and data versioning concepts
• Integration with Spark, Hive, and Flink
• Performance tuning for large-scale datasets
Course Outcome
Upon completion of this training, participants will be able to design and manage modern data lakehouse solutions using Apache Iceberg. They will be capable of building scalable, versioned, and high-performance data tables for analytics and big data processing.
Course Outline
Introduction to Apache Iceberg and Lakehouse Architecture
• Overview of data lakes vs lakehouse architecture
• Apache Iceberg fundamentals and components
• Table format structure and metadata layers
• Setting up Iceberg environment with Spark/Hadoop
Iceberg Table Design and Data Modeling
• Creating and managing Iceberg tables
• Schema design and evolution techniques
• Partitioning strategies for performance optimization
• Writing and reading data using Iceberg
Advanced Iceberg Features and Data Management
• Time travel and snapshot management
• Data versioning and rollback mechanisms
• Query optimization and metadata pruning
• Handling large-scale datasets efficiently
Integration and Production Best Practices
• Integration with Spark, Hive, and Flink
• Catalog management and table maintenance
• Performance tuning strategies
• Best practices for production lakehouse environments
Assessment Topics
• Iceberg architecture and metadata management
• Table design and schema evolution
• Partitioning and query optimization
• Time travel and versioning
• Integration with big data engines
• Lakehouse architecture concepts
Evaluation
• Hands-on Iceberg table creation exercises
• Schema evolution and time travel tasks
• Practical Spark integration assignments
• Mini project on lakehouse data pipeline design
Course Materials
Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.
Certification
Participants who successfully complete the training will receive an AcadNXT Certification in Apache Iceberg Training, validating their expertise in lakehouse architecture, open table formats, data versioning, and scalable big data processing using Apache Iceberg.
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What Our Students Say
“The Iceberg training was very practical and helped me understand modern lakehouse concepts clearly.”
“Excellent hands-on sessions covering schema evolution and time travel features.”
“The course made data lakehouse architecture and Iceberg concepts very easy to understand.”
“Very structured training with strong focus on real-world data lake implementations.”
“This course gave me strong confidence in building modern scalable data lake systems.”