The article discusses the challenges of ensuring data quality compared to code quality, highlighting that detecting, understanding, fixing, and reducing data quality issues are harder than their counterparts in software engineering. It argues that while both involve meeting expectations, data is more complex due to its size, rapid changes, and dependencies. The article also explores the difficulty of debugging data quality issues, as well as strategies for improving data architecture to reduce such issues.