BARC: The Rising Imperative for Data Observability

As demand for analytics and AI accelerates, many organizations still struggle with poor data quality, pipeline bottlenecks, and unreliable model outputs. This independent research by BARC explains why data observability is becoming a must-have capability—and how organizations can build effective programs to stay ahead.

About the research

This report defines what a modern data observability program looks like and outlines the key trends shaping the space in 2025. It includes real-world use cases, survey findings, and actionable recommendations for data leaders—from detection and assessment to issue resolution and governance alignment.

Whether you’re just starting or scaling your observability efforts, this guide offers a clear roadmap.

Get your copy and learn:

1. Why 42% of organizations still don’t trust their AI/ML outputs
2. The top challenges data teams face when scaling observability
3. Key program elements: how to detect, assess, and resolve issues
4. Practical use cases from manufacturing and e-commerce
5. How to extend observability to unstructured data and GenAI workflows

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