Barr Moses - #TrueDataOps Podcast Ep.14

“The problem of data trust is ubiquitous. The number one thing people told us was ‘the data is wrong and that leads us to a place where we can’t trust it, and we can’t use it…’”

In this episode, data observability pioneer, CEO, and co-founder of Monte Carlo, Barr Moses, explores the emergence of data observability and its critical role in modern DataOps. She describes her journey from experiencing frequent data errors at Gainsight to founding a company that addresses data downtime and trust issues. Moses outlines five pillars of data health, which include freshness, volume, schema, quality, and lineage, to help teams automate oversight. The discussion also highlights how these concepts support data mesh architectures by ensuring reliability in decentralized environments.

“We can’t afford to ignore the implications of bad data - and this is where data observability comes in. Today, you not only have a lot more data, you also have a lot more people using the data…”