Wrapping up Season 1, Open||Source||Data producer Audra Montenegro Carter joins Sam Ramji in a conversation about the inspiration and behind-the-scenes production of the podcast, touching upon the top takeaways and lessons learned with Season 1 guests from AWS, Microsoft, Deloitte, Observable, and much more.

Open Source Data

Sam: Hi, this is Sam Ramji and you're listening to Open||Source||Data. This episode, we are going inside the studio and open sourcing the production process behind open source data. I'll be interviewing Audra Montenegro. The instigator and producer of the show. Audra traveled the world with O'Reilly Media, a well-oiled event production machine producing conferences, anywhere from 700 to 6,000 live attendees. Audra managed to on the upwards of 300 speakers per event, she has learned to communicate and spread ideas from engineers, practitioners, and leaders in spaces like dev ops, software architecture, big data analytics and AI.
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Now part of the team here at DataStax with me, Audra is producing this podcast among other event like experiences, which in the past year has been all virtual Audra. I'm excited to flip the script with you. Welcome.&nbsp;
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Audra: Thanks, Sam. I appreciate coming out from behind the curtain.&nbsp;
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Sam: It's so great to have you. I think so many people have been looking for new ways to communicate. I think a lot of folks are trying to figure out, should I start a podcast? What's it like? So the opportunity to interview you and have people understand, what does it take to produce a high quality podcast is going to be super relevant. But as you know, we like to start out with the question. What does open source data mean to you?
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Audra: Yeah, well, Sam. It means this podcast to me and all the people in the surrounding communities. So whether they be our friends or people we're itching to meet, from now on it will forever be the time I got to be the fly on the wall for all these recorded conversations with these leaders that are so well versed in their specific data related expertise.
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Sam: Well, it's been a totem that you've been able to create great relationships and new friendships as well. I think a lot of people are inspired by the idea of open source data. And that was something that you came up with us. You instigated this back in June of last year.&nbsp;
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So I met you back in 2015 at OSCON and we've stayed connected ever since. Thankfully you decided to join me at DataStax when O'Reilly decided to shutter their in-person events. Tell us about what the transition into digital events has been like for you.
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Audra: &nbsp;Both challenging and rewarding at the same time. Challenging because I personally thrive off people's energy and not to be surrounded by it, whether I'm pre, mid, or post event, is kind of odd for me.
Also, the opportunities to be heard simply by posture when you're in person, or to be present without having to look at someone's face, or feeling watched at the same time on zoom video, as well as the lack of resonance in a room when you're really focused in, on a project with somebody. And, being in person just kind of opens up a lot more opportunity to joke around with somebody and just be a little more lighthearted.
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So those interactions, of course, I miss, and I think many other people feel the same way. Right? But what I've appreciated going virtual with events and different experiences like this podcast is being able to flex new muscles. So like video production, for example, or creating thematic stories with our virtual accelerate event, we did last year at DataStax. And getting uncomfortable and coming out the other end, a failed project, for example... coming out. alright because of the insight and expertise that were provided from that experience.
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Sam: What's the biggest thing that you would teach someone else who's starting a non-physical communication, whether it's a podcast or a video series?&nbsp;
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Audra: Well, the biggest tip I would give is, not doing it by yourself. Go interview somebody who's done it and listen to many other podcasts because there are different ways of doing it. You could do seasons, you could not do seasons. You could have a cadence of weekly or biweekly, or you can have different hosts too, but it all depends on what your goal is for the podcast and its audience.
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Sam: Yeah, I think we spent a couple of months thinking through the design and really chewing on what was the philosophy? What kind of conversations do we want to host? So you put a lot of really excellent design work upfront, and frankly that was needed for me as an introvert to convince me to be your minion on the show.
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Thank you for the thoughtfulness and design. I do think that was something I learned. That a podcast is not something that you just kind of hop on and you say, this is a radio show, but there's a lot of upfront design. And then a lot of between sessions legwork, both identifying who are our speakers?
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How do we know them? How do we understand them better? How do we make it a showcase on the person and what they're curious about and what they're excited to share?&nbsp;
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Audra: &nbsp;Absolutely. And. You as a host, I thought was going to be easy because not only do you have a lot of friends in the industry. And I too, are lucky to get a lot of friendships through O'Reilly media events. It's easy to talk to you because you're very thoughtful in your delivery and in every conversation you have. So just building a relationship each time we have a guest on the podcast, you know, whether it's a meet and greet or any other interaction before, and you're like, "Hey, I really want this person on the podcast because of&nbsp; XYZ."&nbsp;
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And you're thoughtful too, with working around the outside of each episode and really just honing in on what is the main takeaway here? What's the message for our audience?&nbsp;
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Sam: Well, talking to him about guests is a great segue. I'd love to take some time to talk about season one on open-source data and what stood out for you about it? The conversations we had.
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Audra: Well, producing a podcast to me is like curating an interesting keynote at a conference. And at the same time, reading a story to my toddler.
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What I mean here is you get to have all these technical conversations with forward thinkers on key topics that affect a strong data architecture. So like Kubernetes meshes fabrics, knowledge graphs, open source in academia. And of course science and analytics.
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And the best part, in my opinion, there's always a community piece and a mentorship piece, and there's always talk on better collaboration practices and that's the heart of open source, right? That's personally what I loved from working at O'Reilly media was just sharing and spreading the knowledge of these innovators.
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We got to bring in folks like Zhamak Dehghani who gave us insight into a Data Mesh, and then talked to Dave Thomas from Deloitte about Data Fabrics. And it was really cool to see the differences there and the like-minded piece of the bigger goal, right.&nbsp;
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Or, talk about data on Kubernetes with folks like Kelsey Hightower and Lachlan Evanson.
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Then there's the DevOps and Observability piece that we got insight from Rachel Chalmers and Melody Meckfessel.
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And then also contrast between data science and data analytics, which Margot Gerritsen, I always pronounce her last name wrong, but you're really good at&nbsp;
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Sam: [Hair-It-Son]. It's a lovely Dutch name.
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Audra: &nbsp;[Mar-Hote-Cha]&nbsp; [Hair-It-Son]&nbsp;
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and Karen Jean-Francois. They're both podcast hosts and have a ton of insight on not only analytics versus data science, but also being a woman in the industry as well. And&nbsp; any struggles and positive outcomes that have come from their tenure in their spaces?&nbsp;
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Sam: Jesse Anderson contributed to kind of that distinction of data science versus data engineering versus data ops as well.
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Audra: That's right. He was a great summarization of all of that.
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Sam: Almost like he wrote a book.
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I love that we started with Patricia Boswell, a staff technical writer at Google and framing human beings as story making machines, uh, which definitely speaks to me poetically. But then she also spoke to the engineer in me by saying "these stories are unit tests for ideas", but that was awesome.
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Audra: Right. And it not only lends itself to technical teams, but a podcast. We're here to tell a story, right?
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Sam: Yeah. And I thought the heart of the principals we&rsquo;re bringing were really well stated by Matt Asay when he said your voice matters. And we need to hear from everyone just kind of trust that you can speak and be listened to. There's, I think a lot of empowerment in open source and Matt has lived in Milwaukee for a long time.
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Audra: He really brought in a perspective of many different communities in the open source world and the dynamic that each one has.
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Sam: If I were starting a podcast, which I never would without you, I would be nervous that I could actually have enough guests on the show. And one of the things that's been really a thrill for me is how many new people I've met because of your outreach. So talk to us a little bit about how you think about your day to day sourcing new people and engaging them.
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Audra: I like to think of myself as a stalker, you know, constantly listening into other people's conversations and what's the next up and coming topic, or what are we double clicking on in terms of the importance in data and open source data, especially. So thankfully we have great community folks here at DataStax and their insight has been awesome in terms of suggesting podcast guests. Then also asking each podcast guest who they suggest as well.
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Sam: The old snowballing technique, as they say in journalism, right. If you've interviewed somebody really interesting, the last question you should ask is who else should I speak with? Because interesting people know more interesting people.&nbsp;
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Audra: &nbsp;Right? Exactly. And then too, you know, I have to admit, of course I was sourcing a lot of the people and speakers that I worked with at O'Reilly events, and who stood out from those experiences. And then a lot of paths crossed with other recommendations too. It's like, Oh yeah, I remember that person and how well they delivered. So I'd like to think it's strategic, but it's more of the topic areas and the timeline of when we deliver these episodes that is more strategic.
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Sam: In terms of the actual production process or what's the most difficult part? What would you point people to, if they're getting ready to do their own podcast?
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Audra: The editing. I mean, for the most part, you just want to leave it organic, right? But then sometimes a conversation can trail off . No conversation is perfect, especially if you don't have that preexisting relationship. So just being patient and really loving what you do, and the story that's being told. And working with the guest, and of course the podcast host, and what is the message we're trying to deliver here.
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Sam: One of my big lessons from this is that the natural flow of conversation in the meet and greet sometimes the best pieces come out of that. And not when you're all prepared and you're looking at a document and you're structuring the podcast. So I think for season two, I want to do more recordings of the meeting, greet and figure out how we can add some of those components into their produced show.&nbsp;
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Audra: Absolutely. You're right. Cause that is a lot more organic and it seems to be pretty lively.
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Sam: If you could recommend to our audience one way to digest the content from season one, how would you best love some of these episodes together?
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Audra: We mentioned earlier, folks like Zhamak Dehghani who gave us insight into a Data Mesh, and Dave Thomas from Deloitte who gave us insight into Data Fabrics.
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Also, I would love for folks who are interested in learning about Data on Kubernetes to listen to first Matt Asay, then Kelsey Hightower, then Lachlan, Evenson, and then Patrick McFadin. He had a great closing episode of the year, not necessarily the season, talking about the future of DBAs and SREs. So that was very interesting.
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And then we mentioned earlier about Karen Jean-Francois and Margot Gerritsen together, the contrast of data analytics and data science, and then Jesse Anderson coming in, summing it all up. Those three are a nice listen together, starting with Karen, then going to Margot and then ending with Jesse.
Then looking into the knowledge graph topic, it was great to interact with Dave Thomas and Paco Nathan. So possibly listening to Paco first then Dave second would provide some very forward-thinking strategic insights on responsible AI, security, and team collaboration around data engineering.
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And then Melody Meckfessel. She's a great one that can be paired with, I would say multiple people. I mean, just listen to her by herself because Observability concept is awesome. And if you've had a chance to listen to the other episodes beforehand, it'll really bring it all together.
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But of course, before you start with anything. Like Sam mentioned, Patricia Boswell really iterates the storytelling machine aspect of humans. And, if you want to get a point across, listen to her and learn what's valuable in technical writing.
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I'm sure there are people I missed, like Stephen Jacobs and Margot are also a good pair. If you want to learn more about open source and academia.
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But I'd love to hear your insight Sam and how you would advise people to listen.
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Sam: I think it's a great concept. And I think Melody would love the idea of pairing as she is also an extremely talented wine producer. Few people know this about melody, but she has a label called Poundstone wines, which are really great.
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Audra: I did not know that!
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Sam: Yeah. It's amazing what creative people do in a non-existent free time. But there you go.
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For me, there was kind of a fluid flow through the whole season. So it's a little bit like picking your favorite child. I can't really do it. Right, but it's this sense of the big themes of data on Kubernetes data teams, which I think Jesse Anderson put so well as a nice unifying construct for data engineering, data ops, data scientists, and then data visualization.
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So these things are all. Evidence that the world is changing. What's been fascinating for me is how many folks we've both met a long way who are now all pointing themselves at data. So folks who've been doing computer infrastructure, network infrastructure, or application infrastructure. We're all kind of coming around this sense that like, wow, this is the decade of data.
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Something is really bringing us all together regardless of where we started. And these are really fascinating topics, right? Melody with her experience at Google doing dev ops now leading an Observable focused entirely on data visualization. There's a change that happened in 2020, and I'm fascinated to see what we see and what we learned in season two.
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Audra: Well, can I ask you this then?&nbsp;
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What do you see past 2021 in the world of data? Given all the conversations we just had in season one.
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Sam: I think it's always about people in technology, right? People are changing. They're becoming more able because they're more familiar, but they're also better supported by tools.
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A lot more automation is coming. Uh, we'll talk to Einat Or from Treeverse in season two, we'll talk with BARR, Moses, and I think I'm getting a sense from conversations with them that. Getting more from the people who are capable of thinking about data is really important. We need to build them exoskeletons, make them stronger, make them faster.
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But there's a bigger tooling change that's happening around containerization of data.
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This is a frame that we're borrowing from the containerization of compute to think about how do we commoditize? How do we standardize? How do we let these things flow? We talked about it a little bit. Paco Nathan, and this is early it's emerging, right? The standards have not yet been written, but there's some, so much power available for all of us collectively, if we can spend the next several years, right.
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Establishing standard ways to describe data, to move it around, to make it accessible and to treat it as a first-class citizen within its infrastructures, much like we do with apps and application code today.
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Audra: Wow. Well, I can't wait to be a fly on the wall for those conversations. Season two, coming at you in June.
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Sam: Yeah, absolutely. Well, thank you for being the amazing producer and inspiration and making it happen every two weeks, rain or shine.
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Let me finish with this. As you're aware, we like to ask you to, for, I guess, to be one resource for a piece of advice for the audience. So what's yours.
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Audra: &nbsp;Well, I want to point people to the episodes on those podcasts as a resource, but how about a word of advice instead, which has stuck with me from something that you're saying, and I heard Tim O'Reilly say, and other open source leaders. While things can be done faster on a smaller team, and even as an individual. No one person has all the expertise, insight, or context. So I've learned this the hard way, both professionally and personally work as a team without a doubt were 100% better together.
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Sam: That's awesome. Audra, the transformation that you've led and experienced for yourself personally is an inspiration to me. A year ago, pre COVID you were on fire building all of these live in person events. And that was something that you'd practiced for many years. All of a sudden the walls came down, COVID changed, right? O'Reilly's strategy changed and you changed with it all, and that takes a tremendous amount of personal courage. You've been a constant inspiration to me. So I'm so privileged to work with you.
 Audra: Oh, the pleasure is absolutely mine. So thank you for inviting me to do this with you.

A Podcast Series With Charna Parkey

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Season 1 · Episode 15

Open Source Data & It's Role in the Future of Technology: Season 1 Recap

Episode Guests

Audra Montenegro

Sam Ramji

Episode Transcript