Data Mesh

"Data Mesh" may be the trendiest term in data science. What is it and how will its Distributed A.I. transform your organization? The founder of the Data Mesh concept herself, Zhamak Dehghani, explains in this episode.

Zhamak:
• Authored the O'Reilly Media book "Data Mesh" and also co-authored an O’Reilly book on software architecture.
• Is newly the CEO and founder of a stealth tech startup reimagining the future of the data developer experience though the Data Mesh.
• Previously worked as a software engineer, software architect, and as a technology incubation director.
• Holds a Bachelor of Engineering degree in Computer Software from the Shahid Beheshti University in Iran and a Masters in Information Technology Management from the University of Sydney in Australia.

Today’s episode should be broadly interesting to anyone who’s keen to get a glimpse of the future of how organizations will work with data and A.I.

In this episode, Zhamak details:
• What a data mesh is.
• Why data meshes are essential today and will be even more so in the coming years.
• The biggest challenges of distributed data architectures.
• Why now was the right time for her to launch her own data mesh startup.
• Her tricks for keeping pace with the rapid of pace of tech progress.

The SuperDataScience show's available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Data Meshes and Data Reliability

The fun and brilliant Barr Moses joins me this week to detail for us what organization-transforming Data Meshes are, as well as how to track and improve the "Data Uptime" (reliability) of your production systems.

Barr is co-founder and CEO of Monte Carlo, a venture capital-backed start-up that has grown in head count by a remarkable 10x in the past year. Monte Carlo specializes in data reliability, making sure that the data pipelines used for decision-making or production models are available 24/7 and that the data are high quality.

In this SuperDataScience episode, Barr covers:
• What data reliability is, including how we can monitor for the "good pipelines, bad data" problem
• How reliable data enables the creation of a Data Mesh that empowers data-driven decision-makers across all of the departments of a company to independently create and analyze data
• How to build a data science team
• How to get a data-focused start-up off the ground, generating revenue and rapidly scaled up

In addition, Barr took time to answer questions from listeners, including those from Svetlana, Bernard, and A Ramesh. Thanks to Scott Hirleman for suggesting Barr as a guest on the show and thanks to Molly Vorwerck for ensuring everything ran perfectly.

Listen or watch here.