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Apache Iceberg: From Zero to Production Data Lakehouse

MittelSchwierigkeitsgrad

Aktualisiert 06/2026

Build production-ready Apache Iceberg lakehouses: model, migrate, and maintain tables at scale.

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SnowflakeData Engineering

4 Std.

19 Videos

44 Übungen

2,200 XP

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Kursbeschreibung

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.

Voraussetzungen

Introduction to Modern Data Engineering with Snowflake

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 Introduction

What does it mean that Apache Iceberg is an Open Table Format?

The Open Lakehouse

Getting Started: Setting Up Your Apache Iceberg Learning Environment

Modeling Data into an Apache Iceberg Table

Hidden Partitioning in Apache Iceberg Tables

Introduction to Data Modeling Exercise

Chapter 1 Summary

Chapter 1 review - Question 1

Chapter 1 review - Question 2

Chapter 1 review - Question 3

Chapter 1 review - Question 4

Chapter 1 review - Question 5

Kapitel starten

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.

Moving existing data to Iceberg

Moving Existing Tables to Iceberg

Git-like features with Write-Audit-Publish and Branching and Tagging

Safe Experimentation in Apache Iceberg Exercise

Schema Evolution for Iceberg Tables

Partition Evolution for Iceberg Tables

Schema and Partition Evolution Exercise

Chapter 2 Summary

Chapter 2 review - Question 1

Chapter 2 review - Question 2

Chapter 2 review - Question 3

Chapter 2 review - Question 4

Chapter 2 review - Question 5

Kapitel starten

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.

Ingesting Data into Apache Iceberg

Copy on Write and Merge on Read

Handling Concurrency in Apache Iceberg

Ingestion Exercise

Table Maintenance for Iceberg - The Basics

Table Maintenance for Iceberg - Compaction and Abandoned File Cleanup

Maintenance Exercise

Writing efficiently to Iceberg Tables

Sort Orders

Advanced Modeling and Ingestion Exercise

Chapter 3 Summary

Additional Resources

Apache Iceberg Course Glossary

Chapter 3 review - Question 1

Chapter 3 review - Question 2

Chapter 3 review - Question 3

Chapter 3 review - Question 4

Chapter 3 review - Question 5

Kapitel starten

Apache Iceberg: From Zero to Production Data Lakehouse

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