<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Streaming on Jaehyeon Kim</title><link>https://jaehyeon.me/tags/streaming/</link><description>Recent content in Streaming on Jaehyeon Kim</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>Copyright © 2023-2026 Jaehyeon Kim. All Rights Reserved.</copyright><lastBuildDate>Fri, 22 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://jaehyeon.me/tags/streaming/index.xml" rel="self" type="application/rss+xml"/><item><title>Current London 2026: Building End-to-End Data Lineage</title><link>https://jaehyeon.me/blog/2026-05-22-end-to-end-data-lineage/</link><pubDate>Fri, 22 May 2026 00:00:00 +0000</pubDate><guid>https://jaehyeon.me/blog/2026-05-22-end-to-end-data-lineage/</guid><description>This week, I traveled to London to speak at Current 2026. In addition to connecting with fellow data practitioners, I presented a session on a common architectural challenge: tracking the complete lifecycle of data.
In modern data ecosystems, understanding data provenance, transformation steps, and final destinations is necessary for governance and root-cause analysis. My session, Building End-to-End Data Lineage with Kafka, Flink, and Spark, detailed a way to capture this metadata across parallel pipelines using OpenLineage.</description><enclosure url="https://jaehyeon.me/blog/2026-05-22-end-to-end-data-lineage/featured.jfif" length="85628" type="image/jpeg"/></item></channel></rss>