Data Debt : The Hidden Malaise Impacting Your Business
Exploring how hidden data quality issues silently erode business metrics — and strategies to detect, prevent, and fix data debt at scale.
In this talk, Sayantan will draw upon a decade of experience working on ML Platforms & Big Data to talk about an often-overlooked challenge in big data systems: data debt. Unlike software outages, data debt is much harder to detect—pipelines may look healthy, jobs may be running fine, but the quality of data silently degrades. This hidden degradation can lead to real-world business impact and drops in user-facing metrics without obvious signals.
He’ll share real-world stories from operating data platforms at massive scale—how data debt creeps in, why traditional monitoring fails to catch it, and what strategies teams can use to build more resilient data systems. His goal is to help practitioners recognize the subtle but critical ways data debt shows up, and walk away with practical insights they can apply in their own environments and build a culture of data debt awareness.