oreilly-author
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Barr Moses
Barr Moses is the co-founder and CEO of Monte Carlo, the company that created the data observability category and built one of the first end-to-end platforms for catching what she named 'data downtime' - the stretches when data is wrong, missing, or simply not trustworthy. A Stanford-trained mathematician and former Israeli Air Force intelligence data unit commander, she went from Bain consulting and a VP role at Gainsight to building a data reliability company valued at $1.6 billion. She co-authored O'Reilly's 'Data Quality Fundamentals' and is one of the most cited voices on why enterprises should treat broken data like broken software.
Shreya Shankar
Shreya Shankar is a PhD candidate at UC Berkeley's EPIC Lab building AI-powered data systems that are reliable and cost-efficient. A Stanford-trained engineer who worked at Google Brain and Meta, she bridges academic research and industry practice through DocETL (an open-source LLM data processing system with 3.5K+ GitHub stars used by 30+ S&P 500 companies), an O'Reilly book on AI evals co-authored with Hamel Husain, and a Maven course that has reached 4,500+ professionals. She is on the CS faculty job market and gave a faculty candidate talk at Carnegie Mellon in March 2026.