『The Data Quality Myth: Why Cleaning Data Never Fixes the Process That Dirtied It』のカバーアート

The Data Quality Myth: Why Cleaning Data Never Fixes the Process That Dirtied It

The Data Quality Myth: Why Cleaning Data Never Fixes the Process That Dirtied It

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Every organization has a data quality problem. Business leaders see incorrect records, duplicate customers, and missing fields—and assume IT can fix it. IT teams know the data isn't the root cause; it's the output of broken workflows, missing ownership, and incentives that reward speed over accuracy. This episode flips the conversation. Mirko Peters explains why data quality is a business process problem wearing an IT costume, why cleaning data without changing the process is like mopping the floor while the tap keeps running, and how to stop the cycle. You'll learn how to define data ownership, how to turn data quality into a process requirement instead of a fire drill, and why the real fix often has nothing to do with technology. Practical, direct, and grounded in real consulting experience.

Become a supporter of this podcast: https://www.spreaker.com/podcast/business-it-it-business--6867401/support.

To continue the conversation, follow Mirko Peters on LinkedIn, where more insights and real-world examples are shared from both business and IT perspectives.
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