The Sequel Show

This week I'm joined by Jessica Cherny, senior data analyst at Ironclad. Jessica is an amazing example of how to foster a genuine presence on the internet while building a career in data, and her episode is great one for folks looking to get into data or those who are at the beginning of their data careers. We touched on a lot of an interesting highlights from Jessica's education, career, and day-to-day data work, including how (and why) she joined Ironclad as a data team of one, why she created her community Data Angels (which is another amazing resource for women in data), and her recommendations for folks looking to break into the field.

This week I’m joined by one of my favorite data leaders, Egor Gryaznov, the co-founder and CTO of data observability company Bigeye. The thread that connected our conversation this episode was what it means to work with a "keeping the lights on" perspective in data, but we touched on a lot of great material, including Egor's time at Uber, how his first company convinced him to join their data team, how we can leverage computer engineering principles in data (and beyond), data warehouse planning, and the future of Bigeye.

In this week's episode, I sat down (virtually) with Marc Stone, head of the analytics team at ClickUp. Marc truly understands the challenges of going from being the only person working on data to running a very large data team and we tapped into his experience to extract some awesome lessons from his career. Some of the high points include topics like what private companies can learn from governments and nonprofits, how to think about data pipelines (especially when there's a human in the mix), how to architect your systems for speed and robustness, how to stay ahead of your users' needs, and what the appropriate data team size is for your maturity level.

Before we get into the episode notes, I want to take a beat to thank all of you for supporting the Show over the last year. It's been amazing watching it go from a fun way to connect with some of my favorite folks in data to a full, polished podcast (featuring even more awesome people). We couldn't do it without you and I'm looking forward to giving the best and brightest of our industry the stage in the coming year. 

To kick things off with season 2, we have a great episode with Jeremiah Lowin, founder and CEO of dataflow automation tool Prefect. In this 1-hour, 7-minute episode, Jeremiah and I dive into the lessons that the wider data industry can learn from the experts in data finance. Some of the major points include:

How he got his start in data finance

The difference in reporting in terms of uncertainty vs outcomes

The case for hearing/focusing on problems vs solutions

Building non-political organizational culture

Non-managerial growth in data careers

As always, let me know what you think of the newest episode over on Twitter at @borisjabes. 

Resources:

Prefect’s Website: https://www.prefect.io/

Find Jeremiah on Twitter:https://twitter.com/jlowin

Find Jeremiah on Linkedin: https://www.linkedin.com/in/jlowin/

Prefect’s Linkedin: https://www.linkedin.com/company/prefect/

Prefect’s Twitter: https://twitter.com/PrefectIO

Music by the talented Joe Stevens: https://www.joestevenssound.com/

Know someone you think would make an awesome guest on the podcast (you can totally nominate yourself, too)? Send your suggestions to our content and community team.

In today’s episode, I talk with Erik Bernhardsson, the former CTO at Better.com and early engineering manager at Spotify. We talked about how to build recommendation systems (including whether you should build them at all). We also covered some best practices on building and scaling data teams, what the essence of music is, and whether data teams should be thought of as an engineering discipline (and what programming languages we should embrace in the data world). We also took a deep dive into how to manage and govern the data team and how to measure the impact. 

Also - if you're looking to stay up to date on the best and most colorful data industry commentary between episodes, check out our new newsletter: The Operational Analytics Diggest. 

Resources:

Erik’s Website: https://erikbern.com/

Find Erik on Twitter:https://twitter.com/bernhardsson

Find Erik on Linkedin: https://linkedin.com/in/erikbern/

Erik’s Github: https://github.com/erikbern

Music by the talented Joe Stevens: https://www.joestevenssound.com/

In today’s episode, I talk with Benn Stancil, chief analytics officer & co-founder at Mode. Honestly, this might be my favorite episode of the Show to date. We had a hearty discussion about data teams and Benn's perspective as someone who started his career as an analyst with an economics degree. Our conversation turned to more philosophical notes around what makes a data professional persuasive (and why that matters), why being wrong is OK (and sometimes a pivotal part of a successful career), and the function of data teams in organizational decisions. 

As always, if you enjoyed this episode, please share it with a data-loving friend and let me know your thoughts on our discussion over on Twitter at @borisjabes. 

Resources:

Benn‘s Substack: https://benn.substack.com/

Find Benn on Twitter:https://twitter.com/bennstancil

Find Benn on Linkedin: https://www.linkedin.com/in/benn-stancil/

Find Mode on Linkedin: https://www.linkedin.com/company/mode-analytics/

Mode’s site: https://mode.com/

Music by the talented Joe Stevens: https://www.joestevenssound.com/

In today’s episode, I talk with Lior Gavish, the co-founder and CTO of Monte Carlo. We talk about his security background, his previous company Sookasa, and the origin story of Monte Carlo, and much more (including the infamous data mesh). We also get into managing and detecting operational issues, what data managers should learn before installing alarms, and what it means to think with a “failure is a feature, not a bug” mindset. Bonus: If you’ve ever wondered if it’s better to be wrong consistently or randomly by 1%, we talk about that, too.

Resources:

Monte Carlo’s site: https://www.montecarlodata.com/about-us/

Connect with Lior on Linkedin:https://www.linkedin.com/in/lgavish/

Find Monte Carlo on Twitter: https://twitter.com/montecarlodata

Find Monte Carlo on Linkedin: https://www.linkedin.com/company/monte-carlo-data/

Music by the talented Joe Stevens: https://www.joestevenssound.com/

Well, Sequel Show fans, we officially have some amazing theme music. Huge thanks to the talented Joe Stevens for our new theme song that makes all my synth-wave dreams come true. 

In today’s episode, I talk with Stefania Olafsdottir, the co-founder and CEO of product analytics platform Avo. We covered an amusing amount of ground--as always in The Sequel Show--from the etymology of cow vs beef to the visualization of weather data. The meat of the show focuses on Stef’s early background as an associate researcher to the accuracy and specificity (or lack thereof) of data role titles today. We dive into the influences of data teams on their companies, how these teams evolve, and the facts, assumptions, and suggested actions these data champions can present. Don’t worry, we also discussed Stef’s experience as the CEO of Avo and took a look at how the company got its start (and her vision for the future of Avo). You don’t want to miss it.

Resources:

Avo’s site: https://www.avo.app/

Connect with Stef on Linkedin: https://www.linkedin.com/company/avohq/

Find Avo on Twitter: https://twitter.com/avohq

Find Avo on Instagram: https://www.instagram.com/avohq/

Music by the talented Joe Stevens: https://www.joestevenssound.com/

In our latest episode, analytics engineer and community builder extraordinaire Claire Carroll sat down with us to talk about her journey from data analyst to analytics engineer to co-founder of analyticsengineers.club, an educational community for aspiring AEs. We cover a lot of ground, discussing her data-industry origin story, the fundamentals the next generation of AE should have in their toolkit, and the goals of her new training course. More broadly, Claire breaks down the gaps in the current data ecosystem and the difference between being a data consumer and a data creator. It's an episode you're not going to want to miss out on.

As always, let me know what you think over on Twitter at @borisjabes.

In this live episode with Snowplow CEO and Co-founder Alex Dean, we dive into all things Snowplow and data collection. Alex runs us through the history of Snowplow--how the company was born and how it evolved--as well as what parts of the platform have grown in complexity. We break down what it means to think about events in a mind-frame of abundance vs scarcity, how to adapt to ever-changing regulations around privacy, and data architecture and infrastructure best practices. Alex rounds the discussion out with some advice on how to approach anonymous users over the next five years, and what a world where the warehouse is a single entity means for post-collection data structures. 

Let me know what you think over on Twitter at @borisjabes.