After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
Course Description
Data lakes promised cheap, flexible storage at scale, but they left engineers fighting broken queries, painful schema changes, and no reliable way to update data. Apache Iceberg fixes that by bringing database-grade reliability to the data lake. In this course, you'll build production-ready Iceberg lakehouses from the ground up: model and partition data for fast queries, migrate existing tables without downtime, evolve schemas and partitions safely with Git-like workflows, and keep everything performant through compaction, snapshot management, and smart write strategies. By the end, you'll be ready to design and operate a modern lakehouse with confidence.
Feels like what you want to learn?
Start Course for FreeWhat you'll learn
- Differentiate Apache Iceberg's open table format and metadata architecture from traditional data lakes, and explain how it delivers database-style reliability and file skipping.
- Determine how to model and partition Iceberg tables with hidden partitioning so queries prune the files they don't need.
- Identify the right strategy for migrating existing Parquet, ORC, Hive, or database data into Iceberg without rewriting everything.
- Assess when to use Write-Audit-Publish, branching, and tagging to evolve schemas and partitions safely on live tables.
- Evaluate write strategies, concurrency, and maintenance operations such as compaction and snapshot expiration for keeping production Iceberg tables fast at scale.
Prerequisites
Curriculum
Course outline
1
Apache Iceberg Fundamentals
In this chapter, learn how to set up an Apache Iceberg lakehouse and model data with hidden partitioning so your queries skip the files they don't need.
- Course Introduction50 XP
- What does it mean that Apache Iceberg is an Open Table Format?50 XP
- The Open Lakehouse50 XP
- Getting Started: Setting Up Your Apache Iceberg Learning Environment50 XP
- Modeling Data into an Apache Iceberg Table50 XP
- Hidden Partitioning in Apache Iceberg Tables50 XP
- Introduction to Data Modeling Exercise50 XP
- Chapter 1 Summary50 XP
- Chapter 1 review - Question 150 XP
- Chapter 1 review - Question 250 XP
- Chapter 1 review - Question 350 XP
- Chapter 1 review - Question 450 XP
- Chapter 1 review - Question 550 XP
2
Taking Advantage of Apache Iceberg Tables
In this chapter, learn how to migrate existing data into Iceberg and safely evolve schemas and partitions using Git-like workflows such as Write-Audit-Publish, branching, and tagging.
3
Operating and Optimizing Apache Iceberg
In this final chapter, learn how to keep production Iceberg tables fast at scale through smart write strategies, safe concurrency, and maintenance operations like compaction and snapshot expiration.
R
Apache Iceberg: From Zero to Production Data Lakehouse
Course
Complete
