Summary

The data ecosystem has seen a constant flurry of activity for the past several years, and it shows no signs of slowing down. With all of the products, techniques, and buzzwords being discussed it can be easy to be overcome by the hype. In this episode Juan Sequeda and Tim Gasper from data.world share their views on the core principles that you can use to ground your work and avoid getting caught in the hype cycles.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management
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Your host is Tobias Macey and today I'm interviewing Juan Sequeda and Tim Gasper about their views on the role of the data mesh paradigm for driving re-assessment of the foundational principles of data systems

Interview

Introduction
How did you get involved in the area of data management?
What are the areas of the data ecosystem that you see the most turmoil and confusion?
The past couple of years have brought a lot of attention to the idea of the "modern data stack". How has that influenced the ways that your and your customers' teams think about what skills they need to be effective?
The other topic that is introducing a lot of confusion and uncertainty is the "data mesh". How has that changed the ways that teams think about who is involved in the technical and design conversations around data in an organization?
Now that we, as an industry, have reached a new generational inflection about how data is generated, processed, and used, what are some of the foundational principles that have proven their worth?
- What are some of the new lessons that are showing the greatest promise?
- data modeling
- data platform/infrastructure
- data collaboration
- data governance/security/privacy
How does your work at data.world work support these foundational practices?
- What are some of the ways that you work with your teams and customers to help them stay informed on industry practices?
- What is your process for understanding the balance between hype and reality as you encounter new ideas/technologies?
What are some of the notable changes that have happened in the data.world product and market since I last had Bryon on the show in 2017?
What are the most interesting, innovative, or unexpected ways that you have seen data.world used?
What are the most interesting, unexpected, or challenging lessons that you have learned while working on data.world?
When is data.world the wrong choice?
What do you have planned for the future of data.world?

Contact Info

Juan
- LinkedIn
- @juansequeda on Twitter
- Website
Tim
- LinkedIn
- @TimGasper on Twitter
- Website

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
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Links

data.world
- Podcast Episode
Gartner Hype Cycle
Data Mesh
Modern Data Stack
DataOps
Data Observability
Data & AI Landscape
DataDog
RDF == Resource Description Framework
SPARQL
Moshe Vardi
Star Schema
Data Vault
- Podcast Episode
BPMN == Business Process Modeling Notation

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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