Apache Iceberg Training Course

8 Lesson

30 Hours

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igmGuru offers the best Apache Iceberg Training Program worldwide for learners of all levels. Our training includes key topics such as Iceberg architecture, catalog configuration, schema and partition evolution, ACID transactions, time travel and versioning, integration with Spark, Flink, and Trino, real-time data ingestion, and much more. The Apache Iceberg certification course content is designed by industry experts with over 10 years of experience in big data engineering, cloud data platforms, and analytics implementation

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Apache Iceberg Course Overview

Enroll now in our Apache Iceberg Course to gain hands-on experience through live interactive sessions, real-world projects, and personalized mentorship. The course is fully aligned with modern data lakehouse and open data ecosystem best practices, enabling you to confidently build, manage, and optimize Iceberg-based data platforms.

Prerequisites

Basic understanding of databases and SQL
Knowledge of data engineering concepts
Familiarity with cloud storage or the Hadoop ecosystem
Basic knowledge of programming or scripting

What Will You Learn

What is a “data lakehouse” and why it matters
What is a “table format” in the lake context
Overview of Iceberg’s architecture: table metadata, manifest lists, data files, catalog service, layers
Support for ACID transactions, schema & partition evolution
Installation, dependencies & environment (on-prem, cloud object storage: S3/MinIO, etc.)
Integrating with compute engines (Apache Spark, Apache Flink, SQL engines such as Hive/Trino/Presto)
Creating tables: syntax, options, choosing formats (Parquet, ORC, Avro)
Table maintenance: compaction, expiring older snapshots, garbage collection/clean-up
Schema evolution (add/drop/rename fields) and partition evolution
Upserts, deletes, merges (row-level operations)
Optimizing table layout (file sizing, partitioning strategies)
Auditing and metrics: measuring performance, monitoring usage, and setting alerts
CDC support: how Iceberg handles change streams, late data, and merges

Key Features

Flexible Schedule
100% Job Assistance
100% Money-Back Guarantee
24 X 7 Lifetime Support
Experienced & Professional Trainers
1 On 1 Training Option Available

Apache Iceberg Course Modules

Lesson 1 - Introduction to Data Lakehouse & Table Formats

1. What is a “data lakehouse” and why it matters

2. What is a “table format” in the lake context

3. Challenges in traditional data lakes: scalability, metadata, schema evolution, ACID support

4. Why Apache Iceberg – value proposition, use-cases, comparison with formats like Apache Hudi and Delta Lake (e.g., “Iceberg vs Hudi vs Delta”)

Lesson 2 - Architecture of Apache Iceberg

1. Overview of Iceberg’s architecture: table metadata, manifest lists, data files, catalog service, layers (metadata vs data)

2. Components: Catalogs, Table Metadata JSON, Manifest List, Manifest Files, Data Files

3. How Iceberg decouples storage, compute & metadata

4. Support for ACID transactions, schema & partition evolution

5. Under-the-covers: hidden partitioning, time travel, versioning

Lesson 3 - Setting Up & Integrating Iceberg

1. Installation, dependencies & environment (on-prem, cloud object storage: S3/MinIO, etc)

2. Configuring catalogs (e.g., Hadoop, Hive, REST)

3. Integrating with compute engines: e.g., Apache Spark, Apache Flink, SQL engines (Hive/Trino/Presto)

4. Setting up sample workspace / table store

Lesson 4 - Creating & Managing Iceberg Tables

1. Creating tables: syntax, options, choosing formats (Parquet, ORC, Avro)

2. Table properties: partitioning, clustering, file format selection

3. Writing data (batch, streaming) and reading data from tables

4. Table maintenance: compaction, expiring older snapshots, garbage collection / clean-up

Lesson 5 - Data Operations – Advanced Features

1. Schema evolution (add/drop/rename fields), partition evolution

2. Time travel and snapshot queries (querying historical versions)

3. Upserts, deletes, merges (row-level operations)

4. Hidden partitioning, data pruning & performance optimisations

Lesson 6 - Performance Optimisation & Monitoring

1. Optimising table layout (file sizing, partitioning strategies)

2. Monitoring metadata size, manifest lists, scan planning & how to reduce full table scans

3. Auditing and metrics: how to measure performance, monitor usage, set alerts

4. Best practices: compaction, choosing partitioning vs clustering, late-arriving data handling

Lesson 7 - Streaming, Change Data Capture (CDC) & Real-Time Use Cases

1. Using Iceberg in streaming pipelines (Flink, Kafka, Spark Structured Streaming)

2. CDC support: how Iceberg handles change streams, late data, merges

3. Use cases: near-real-time analytics, incremental ETL, updating large tables

4. Hands-on example: ingesting streaming data into Iceberg and querying it

Lesson 8 - Migration, Governance & Catalogs

1. Migrating from legacy systems (e.g., Hive tables) to Iceberg

2. Catalog choices, versioning of tables, branching & tagging (e.g., via Project Nessie)

3. Governance, security (access control, table-level/table-snapshot level), audit trails

4. Data as code: managing metadata alongside code, branching tables, multi-table transactions

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Apache Iceberg Training Fees and Batch Details

Online Class Room Program

US $ 799.00

100% Money Back Guarantee

Duration : 30 Hrs
Plus Self Paced

Classes Starting From

Fast Track Batch 11 Jul 2026
Weekday Batch 13 Jul 2026
Weekend Batch 11 Jul 2026

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Apache Iceberg Certification

Upon successful completion of the Apache Iceberg Training, we will provide a Course Completion Certificate to all learners. This certificate validates your expertise in implementing and managing data lakehouse solutions using Apache Iceberg.

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Apache Iceberg Training Course