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X-ORIGINAL-URL:https://ortech.com.my
X-WR-CALDESC:Events for ORTECH | Engineering Data, Lakehouse &amp; AI for Impact
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TZID:Asia/Shanghai
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DTSTART:20250101T000000
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DTSTART;TZID=Asia/Shanghai:20261007T000000
DTEND;TZID=Asia/Shanghai:20261007T010000
DTSTAMP:20260911T100959Z
CREATED:20260911T090040Z
LAST-MODIFIED:20260911T100959Z
UID:3950-1791331200-1791334800@ortech.com.my
SUMMARY:Workshop: Apache Iceberg in Practice: Build\, Evolve\, and Optimize
DESCRIPTION:Designing high-performance open lakehouse tables is only the starting point. As business requirements pivot\, schema definitions shift\, and data volumes surge\, keeping Apache Iceberg tables performant\, reliable\, and healthy requires a clear operational framework. \n  \nJoin Starburst for an interactive\, hands-on workshop led by Marius Grama\, Engineering Manager at Starburst\, titled “Apache Iceberg in Practice: Build\, Evolve\, and Optimize.” Rather than staying high-level\, this session tracks a single Iceberg table across its complete production lifecycle—from initial creation and data hydration to schema evolution and ongoing table maintenance. \n  \nBy dissecting how Apache Iceberg manages snapshot metadata\, manifests\, and versioning under the hood\, you will walk away with a practical\, step-by-step operating model you can implement immediately within your data lakehouse architecture. \n  \nWhat You’ll Learn: \n\nTable Foundation & Querying: Create\, populate\, and query Apache Iceberg tables designed for enterprise scale.\nUnder-the-Hood Mechanics: Understand exactly how Iceberg stores metadata\, tracks snapshots\, and versions state changes across distributed storage.\nSeamless Schema & Partition Evolution: Alter column schemas and partition specs on the fly—completely eliminating costly\, full-table data rewrites.\nZero-Copy Branching: Leverage Git-like branching in Iceberg to stage\, test\, and validate data modifications safely before merging them into production.\nLong-Term Performance Optimization: Implement maintenance strategies (compaction\, snapshot expiration\, and manifest rewrites) to prevent table degradation as workloads scale.\n\n  \nWhether you are a data engineer\, lakehouse architect\, or analytics platform administrator\, this workshop provides the tactical knowledge needed to build resilient\, self-sustaining Iceberg tables that scale effortlessly.
URL:https://ortech.com.my/event/workshop-apache-iceberg-in-practice-build-evolve-and-optimize/
LOCATION:Live Webinar
CATEGORIES:Startburst Events
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