Joe Reis Flips The Script And Interviews Tobias Macey About The Data Engineering Podcast
Data Engineering Podcast
00:00
Data Engineering Podcast - What's the Future of Hadup?
Five years ago, the hidup ecosystem was still relevant. Now there's not really much conversation happening around that ecosystem. Data quality has gained a lot of ground now that people are able to build systems. You don't have to be in expert in distributed systems to be able to get a distributed system up in running.
Transcript
Play full episode
Transcript
Episode notes
Summary
Data engineering is a large and growing subject, with new technologies, specializations, and "best practices" emerging at an accelerating pace. This podcast does its best to explore this fractal ecosystem, and has been at it for the past 5+ years. In this episode Joe Reis, founder of Ternary Data and co-author of "Fundamentals of Data Engineering", turns the tables and interviews the host, Tobias Macey, about his journey into podcasting, how he runs the show behind the scenes, and the other things that occupy his time.
Announcements
- Hello and welcome to the Data Engineering Podcast, the show about modern data management
- When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Go to dataengineeringpodcast.com/linode today and get a $100 credit to launch a database, create a Kubernetes cluster, or take advantage of all of their other services. And don’t forget to thank them for their continued support of this show!
- RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control. Their SDKs make event streaming from any app or website easy, and their state-of-the-art reverse ETL pipelines enable you to send enriched data to any cloud tool. Sign up free… or just get the free t-shirt for being a listener of the Data Engineering Podcast at dataengineeringpodcast.com/rudder.
- Data teams are increasingly under pressure to deliver. According to a recent survey by Ascend.io, 95% in fact reported being at or over capacity. With 72% of data experts reporting demands on their team going up faster than they can hire, it’s no surprise they are increasingly turning to automation. In fact, while only 3.5% report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. 85%!!! That’s where our friends at Ascend.io come in. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java. Ascend automates workloads on Snowflake, Databricks, BigQuery, and open source Spark, and can be deployed in AWS, Azure, or GCP. Go to dataengineeringpodcast.com/ascend and sign up for a free trial. If you’re a data engineering podcast listener, you get credits worth $5,000 when you become a customer.
- Your host is Tobias Macey and today we’re flipping the script. Joe Reis of Ternary Data will be interviewing me about my time as the host of this show and my perspectives on the data ecosystem
Interview
- Introduction
- How did you get involved in the area of data management?
- Now I’ll hand it off to Joe…
Joe’s Notes
- You do a lot of podcasts. Why? Podcast.init started in 2015, and your first episode of Data Engineering was published January 14, 2017. Walk us through the start of these podcasts.
- why not a data science podcast? why DE?
- You’ve published 306 of shows of the Data Engineering Podcast, plus 370 for the init podcast, then you’ve got a new ML podcast. How have you kept the motivation over the years?
- What’s the process for the show (finding guests, topics, etc….recording, publishing)? It’s a lot of work. Walk us through this process.
- You’ve done a ton of shows and have a lot of context with what’s going on in the field of both data engineering and Python. What have been some of the major evolutions of topics you’ve covered?
- What’s been the most counterintuitive show or interesting thing you’ve learned while producing the show?
- How do you keep current with the data engineering landscape?
- You’ve got a very unique perspective of data engineering, having interviewed countless top people in the field. What are the the big trends you see in data engineering over the next 3 years?
- What do you do besides podcasting? Is this your only gig, or do you do other work?
- whats next?
Contact Info
Closing Announcements
- Thank you for listening! Don’t forget to check out our other shows. The Data Engineering Podcast covers the latest on modern data management. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used.
- Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
- If you’ve learned something or tried out a project from the show then tell us about it! Email hosts@themachinelearningpodcast.com) with your story.
- To help other people find the show please leave a review on iTunes and tell your friends and co-workers
Parting Question
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
Links
- Podcast.__init__
- The Machine Learning Podcast
- Ternary Data
- Fundamentals of Data Engineering book (affiliate link)
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.
