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Paving The Road For Fast Analytics On Distributed Clouds With The Yellowbrick Data Warehouse

Summary

The data warehouse has become the focal point of the modern data platform. With increased usage of data across businesses, and a diversity of locations and environments where data needs to be managed, the warehouse engine needs to be fast and easy to manage. Yellowbrick is a data warehouse platform that was built from the ground up for speed, and can work across clouds and all the way to the edge. In this episode CTO Mark Cusack explains how the engine is architected, the benefits that speed and predictable pricing has for the organization, and how you can simplify your platform by putting the warehouse close to the data, instead of the other way around.

Announcements

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Your host is Tobias Macey and today I’m interviewing Mark Cusack about Yellowbrick, a data warehouse designed for distributed clouds

Interview

Introduction
How did you get involved in the area of data management?
Can you start by describing what Yellowbrick is and some of the story behind it?
What does the term “distributed cloud” signify and what challenges are associated with it?
How would you characterize Yellowbrick’s position in the database/DWH market?
How is Yellowbrick architected?
How have the goals and design of the platform changed or evolved over time?

How does Yellowbrick maintain visibility across the different data locations that it is responsible for?
What capabilities does it offer for being able to join across the disparate “clouds”?

What are some data modeling strategies that users should consider when designing their deployment of Yellowbrick?
What are some of the capabilities of Yellowbrick that you find most useful or technically interesting?
For someone who is adopting Yellowbrick, what is the process for getting it integrated into their data systems?
What are the most underutilized, overlooked, or misunderstood features of Yellowbrick?
What are the most interesting, innovative, or unexpected ways that you have seen Yellowbrick used?
What are the most interesting, unexpected, or challenging lessons that you have learned while working on and with Yellowbrick?
When is Yellowbrick the wrong choice?
What do you have planned for the future of the product?

Contact Info

LinkedIn
@markcusack on Twitter

Parting Question

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

Links

Yellowbrick
Teradata
Rainstor
Distributed Cloud
Hybrid Cloud
SwimOS
Podcast Episode

Kafka
Pulsar
Podcast Episode

Snowflake
Podcast Episode

AWS Redshift
MPP == Massively Parallel Processing
Presto
Trino
Podcast Episode

L3 Cache
NVMe
Reactive Programming
Coroutine
Star Schema
Denodo
Lexis Nexis
Vertica
Netezza
Grenplum
PostgreSQL
Podcast Episode

Clickhouse
Podcast Episode

Erasure Coding

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

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