March was an exciting month with inspiring guests talking about the current state of data and predicting how exciting the future of data will be. We had amazing guests, each with their unique stories – LeafLink, Avo, Ternary Data, Big Time Data, and The Atlantic!
Eric and Kostas discussed:
- How B2B marketplaces help brands manage and track their order and maintain relationships
- Next-Gen Data Governance
- Data Engineering: Present and Future
- Comparing different data stacks – from seed startups to large enterprises
- Data Science in Publication – The Atlantic
Check out interesting highlights from each episode below, and subscribe to get new episodes every week!
B2B Marketplaces for Cannabis with Mike Luby from LeafLink
In this episode, Eric and Kostas talk to Mike Luby, director of engineering at LeafLink, a cannabis industries B2B wholesale marketplace.
Mike kicks off by sharing a brief about LeafLink, its different products so far, and how LeafLink deals with compliance challenges. Structuring the product management teams is crucial, and we’ll see how LeafLink has structured its product engineering organization around business domains. Eric and Kostas had an interesting conversation around LeafLink’s data stack and how it leveraged AWS on a high level and learned about the other tools that fuel the rest of the stack.
We’ll hear how LeafLink plans to move towards an event-driven architecture and train its engineers accordingly. Finally, we get to know how LeafLink exposes APIs to provide critical integrations for customers to automate and optimize their businesses.
Next-Gen Data Governance with Stefania from Avo
In this episode, Eric and Kostas talk to Stefanía Bjarney Ólafsdóttir, CEO and co-founder of Avo. This company offers data analytics governance as a service and helps organizations make data-driven decisions to improve their customer experience.
Stefanía has a fascinating background – studied mathematics (a double in mathematics), worked in bioinformatics, and then into consumer mobile. She shared a bit about the common grounds between mathematics and philosophy, her journey at QuizUp as head of data science, and an exciting story on how she decided to join QuizUp. Her take on the rising importance of product analytics is simple – choose fundamental parts of the customer experience and understand those points very well.
Avo’s mission is to provide analytics governance as a service, and we will see the need behind it and look at a few of Avo’s use cases. Stefanía also highlights how growth is perceived from the CFOs and how non-standard KPIs such as retention and customer satisfaction take center stage.
Upcoming Trends in Data Engineering with Joe Reis and Matthew Housley from Ternary Data
This episode with Matthew Housley, CTO, and Joe Reis, CEO, and co-founder of Ternary Data, focuses on the common trends in the data sphere and how startups and enterprises deal with their data.
Matthew and Joe talk about the evolution in the role of the data engineer. We’ll see how the data engineer role will largely depend on the company’s size and on the scale of the problems they solve in the future.
Joe and Matthew reveal a few upcoming tools and trends and share a classic use case of how ML shapes the data science industry and how it is currently implemented with data. Lastly, they touch upon the concept of real-time and a clear distinction between batch and real-time data.
Learning to Nurture DataStack with Rachel Bradley-Haas and Alex Dovenmuehle of Big Time Data
Alex Dovenmuehle was our very first guest representing Mattermost at the time. In this episode, we welcome him again along with Rachel Bradley-Haas as co-founders of Big Time Data. We’ll learn about their background and their common goal to make data approachable to everyone. Most importantly, we will understand how companies face problems when a data stack isn’t nurtured at an early stage.
Alex and Rachel also discuss the changes in the data stack technology over the years – from their roles at Heroku to Mattermost and Big Time data. They also talk about different client use cases and how these companies deal with their customer data. Lastly, we get to hear amazing comparisons of different data stacks ranging from seed-stage startups to mid-sized companies and established enterprises.
How ‘The Atlantic’ Uses Data with Jenna Lemonias from the Atlantic
‘The Atlantic‘ has been a popular publication serving content for 160 years! In this episode, Eric and Kostas had the privilege of talking to Jenna Lemonias, director of data science at The Atlantic. Jenna talks about her Ph.D. in Astrophysics and how she pivoted towards data science.
Based on her experience working in FinTech, she shares differences in dealing with data in FinTech vs. in a publication firm. She talks about how The Atlantic’s data science and data engineering teams structure their different processes, including collecting raw data, building ETL pipelines and workflow management tools.
Eric and Kostas are fascinated to learn how The Atlantic uses natural language processing and machine-generated metadata and use it to build personalization, power research engines, and so on. Lastly, Jenna talks about ‘The Atlantic’s data stack and what data is most important to them. We also get a sneak-peak into The Atlantic’s roadmap for their data science team’s upcoming projects.
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