DENG-251: Building an Open Data Lakehouse using Apache Iceberg
Course covers Iceberg's benefits, architecture, read/write operations, streaming, and advanced features.
Course Overview
Course covers Iceberg's benefits, architecture, read/write operations, streaming, and advanced features.
The Open Data Lakehouse is a modern data architecture that enables versatile analytics on streaming and stored data within cloud-native object stores. This architecture can span hybrid and multi-cloud environments.
This course introduces Apache Ozone, a hybrid storage service addressing the limitations of HDFS. You'll also explore Apache Iceberg, an open-table format optimized for petabyte-scale datasets. The course covers Iceberg's benefits, architecture, read/write operations, streaming, and advanced features like time travel, partition evolution, and Data-as-Code. Over 25 hands-on labs and a capstone project will equip you with the skills to build an efficient, performant Open Data Lakehouse within your own environment.
Course Objectives
This course teaches participants the following skills:
Gain a deep understanding of Iceberg's benefits, snapshots, and their functionalities.
Confidently build external and managed tables, configuring copy-on-write and merge-on-read for optimized data management.
Perform rollbacks and time travel, navigate schema and partition evolution, and utilize hidden partitions.
Create and merge table branches, mastering Iceberg's write-audit-publish procedure.
Efficiently perform table maintenance tasks and tackle data migration challenges.
Available Options
Upcoming Sessions
0 sessions availableNo Sessions Scheduled
There are currently no upcoming sessions scheduled for this course.
Request Course Information