<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Lars Leipson — Writing</title><description>Articles about data production — what it is, how to build it, and how to organize for it. Operational frameworks from 170+ industries.</description><link>https://larsleipson.com/</link><item><title>What &apos;Data Production&apos; Actually Means</title><link>https://larsleipson.com/writing/what-data-production-means/</link><guid isPermaLink="true">https://larsleipson.com/writing/what-data-production-means/</guid><description>Data production is the discipline of producing business-relevant data at scale for business customers. It is the core capability of any data provider and any Data-as-a-Service business — even though it is rarely recognized as a discipline of its own. What makes it unique is that it requires fluency in five distinct languages: business, industry, data, technology, and leadership. The differentiator isn&apos;t producing any single data type in depth — it&apos;s understanding multi-data-type customer use cases and providing the data that actually drives decisions. In the age of AI, getting any data is becoming easy. Getting the right data stays hard. And as AI puts data into more workflows, the impact of data quality and relevance is increasing.</description><pubDate>Mon, 23 Mar 2026 00:00:00 GMT</pubDate></item></channel></rss>