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The Soda Podcast brings forward different voices and perspectives to help find a common ground to solve the problems that many are facing when it comes to good data. This is a collection of conversations focused on data, and the tools, technologies, methodologies, and people that use it every day. 
The series now available is ‘The Data Dream Team’. Hear guests in conversation on the new approach needed to align how an organization and its people should be structured and organized around data. Visit for complementary content and resources.

Nov 30, 2021

Harvinder Atwal is the Chief Data Scientist at Moneysupermarket Group. Listen to Jesse and Harvinder connect and prepare for their conversation on how Harvinder has applied Lean Thinking, DevOps, and Agile Methodologies, to develop the right organisation and structure for data management and governance.

Nov 25, 2021

Holden Karau is a true champion for open source and becoming a better data engineer. Feel the power of her spark as you hear Holden’s perspective as an individual contributor in a data team, and enjoy as she shares her hobbies, practical advice and approaches to working in data.

Nov 23, 2021

Holden Karau is best known for her work on Apache Spark™, her advocacy for open source software, and her creation and maintenance of a variety of related projects, including spark-testing-base. Get to know Holden before we look at the data dream team from the perspective of an individual...

Nov 18, 2021

A thoughtful conversation examining the paradigm shift and the unlearning required to build a data-driven organization at scale. Hear Zhamak, the founder of data mesh, discuss what data mesh is and what it isn’t. This conversation provides insights, failsafe tips, and inspiration to use data to augment and improve...

Nov 16, 2021

Zhamak Dehghani is a software engineer, architect, and founder of data mesh. Zhamak founded the concept of data mesh as the paradigm shift needed in how we manage data at scale. Meet Zhamak and learn how data mesh will help organizations achieve data-driven value at scale.