Adding An Easy Mode For The Modern Data Stack With 5X

Data Engineering Podcast

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11M ago 56:12

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Summary

The "modern data stack" promised a scalable, composable data platform that gave everyone the flexibility to use the best tools for every job. The reality was that it left data teams in the position of spending all of their engineering effort on integrating systems that weren't designed with compatible user experiences. The team at 5X understand the pain involved and the barriers to productivity and set out to solve it by pre-integrating the best tools from each layer of the stack. In this episode founder Tarush Aggarwal explains how the realities of the modern data stack are impacting data teams and the work that they are doing to accelerate time to value.

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 welcoming back Tarush Aggarwal to talk about what he and his team at 5x data are building to improve the user experience of the modern data stack.

Interview

Introduction
How did you get involved in the area of data management?
Can you describe what 5x is and the story behind it?
- We last spoke in March of 2022. What are the notable changes in the 5x business and product?
What are the notable shifts in the data ecosystem that have influenced your adoption and product direction?
- What trends are you most focused on tracking as you plan the continued evolution of your offerings?
What are the points of friction that teams run into when trying to build their data platform?
Can you describe design of the system that you have built?
- What are the strategies that you rely on to support adaptability and speed of onboarding for new integrations?
What are some of the types of edge cases that you have to deal with while integrating and operating the platform implementations that you design for your customers?
What is your process for selection of vendors to support?
- How would you characterize your relationships with the vendors that you rely on?
For customers who have pre-existing investment in a portion of the data stack, what is your process for engaging with them to understand how best to support their goals?
What are the most interesting, innovative, or unexpected ways that you have seen 5XData used?
What are the most interesting, unexpected, or challenging lessons that you have learned while working on 5XData?
When is 5X the wrong choice?
What do you have planned for the future of 5X?

Contact Info

LinkedIn
@tarush on Twitter

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

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