Josh Patterson (@datametrician, Co-Founder & CEO @VoltronData) talks about the concept of composable data analytics and how it benefits our industry. What is it, why should be using it, and how to get started.

SHOW: 694

CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotw

NEW TO CLOUD? CHECK OUT - "CLOUDCAST BASICS"

SHOW SPONSORS:

• Solve your IAM mess with Strata's Identity Orchestration platform
• Have an identity challenge you thought was too big, too complicated, or too expensive to fix? Let us solve it for you! Visit strata.io/cloudcast to share your toughest IAM challenge and receive a set of AirPods Pro
• How to Fix the Internet (A new podcast from the EFF)
• Datadog Kubernetes Solution: Maximum Visibility into Container Environments
• Start monitoring the health and performance of your container environment with a free 14 day Datadog trial. Listeners of The Cloudcast will also receive a free Datadog T-shirt

SHOW NOTES:

• Voltron Data (homepage)
• Apache Arrow (homepage)
• CRN 10 Hottest Big Data Startups of 2022 (CRN)
• Voltron grabs 110M Series A (TechCrunch)

Topic 1 - Hello Josh and welcome to the show. You have a very diverse and interesting background. Can you give everyone a quick introduction? As a follow up, tell everyone a little bit about your experience as Presidential Innovation Fellow.

Topic 2 - Before we dig into Voltron Data, we need to tell everyone about Apache Arrow. Business and organizations tend to be overwhelmed by big data. Everything from the volume, to the tools, to the lack of data scientists and practitioners. Can you give everyone an overview of Arrow, how it came to be, what problem does it solve? 

Topic 3 - Arrow has companies like Snowflake, NetFlix, Meta, Databricks, Google and Microsoft all adopting it. Our listeners will be more familiar with Snowflake & Databricks and their business models, what makes Voltron Data different? How are you building a company on top of OSS?

Topic 4 - Let’s talk about communities and standards. I’ve seen various numbers on Arrow and monthly downloads, always in the tens of millions per month. Your focus appears to be providing services for Arrow and other Apache projects to simplify open source for those that don’t have the skills or time, while also working towards the goal of community standards. Is that correct?

Topic 5 - How will open source standards for data help the data analytics industry move faster? Is this a process problem? A data set problem? A tools problem?

Topic 6 - Data Analytics has a reputation for a high barrier to entry. If our listeners are interested, how can they get started?

FEEDBACK?

• Email: show at the cloudcast dot net
• Twitter: @thecloudcastnet