Where I express personal thoughts in words
Salma Bakouk is the CEO and co-founder of Sifflet, a Full Data Stack Observability platform. Before Sifflet, Salma was an Executive Director at Goldman Sachs in Sales & Trading in Asia, leading key Data & Analytics initiatives. Salma holds an Engineering Degree from École Centrale Paris in Applied Mathematics and a Master's in Statistics and Data Science.
Alessya Visnjic is the CEO and co-founder of WhyLabs, the AI Observability company on a mission to build the interface between AI and human operators. Prior to WhyLabs, Alessya was a CTO-in-residence at the Allen Institute for AI (AI2), where she evaluated the commercial potential for the latest advancements in AI research.
Earlier in her career, Alessya spent nine years at Amazon, leading Machine Learning adoption and tooling efforts. She was a founding member of Amazon’s first ML research center in Berlin, Germany. Alessya is also the founder of Rsqrd AI, a global community of 1,000+ AI practitioners who are committed to making AI technology Robust & Responsible.
Earlier this month, I attended the second iteration of DataOps Unleashed, a great event that examines the emergence of DataOps, CloudOps, AIOps, and other professionals coming together to share the latest trends and best practices for running, managing, and monitoring data pipelines and data-intensive analytics workloads.
In this long-form blog recap, I will dissect content from the session talks that I found most useful from attending the summit. These talks are from DataOps professionals at leading organizations detailing how they establish data predictability, increase reliability, and reduce costs with their data pipelines. If interested, you should also check out my recap of DataOps Unleashed 2021 last year.
Gleb Mezhanskiy is the CEO & Co-founder of Datafold - a data observability platform that helps companies unlock growth through more effective and reliable use of their analytical data. As a founding member of Data teams at Autodesk and Lyft and the Head of Product at Phantom Auto, Gleb has built some of the world's largest and most sophisticated data platforms and has developed tooling to improve productivity and data quality in organizations with hundreds of data users.
Last week, I attended DataOps Unleashed, a great event that examines the emergence of DataOps, CloudOps, AIOps, and other professionals coming together to aggregate conversations around the latest trends and best practices for running, managing, and monitoring data pipelines.
This long-form blog recap dissects content from the session talks that I found most useful from attending the summit. These talks are from DataOps professionals at leading organizations detailing how they establish data predictability, increase reliability, and create economic efficiencies with their data pipelines.
Barr Moses is the CEO & co-founder of Monte Carlo, a data reliability company committed to accelerating the world’s data adoption by reducing Data Downtime. Monte Carlo is backed by Accel, GGV, and other top Silicon Valley investors, including the former Chief Data Scientist of the U.S., DJ Patil. Previously, Barr was VP Customer Operations at customer success company Gainsight, where she helped scale the company 10x in revenue and, among other functions, built the data/analytics team. Prior to that, Barr was a management consultant at Bain & Company and a research assistant at the Statistics Department at Stanford. She also served in the Israeli Air Force as a commander of an intelligence data analyst unit and graduated from Stanford University with a B.Sc. in Mathematical and Computational Science.
