Straight Data Talk (Yuliia Tkachova)

Andrii Yasinetsky is a serial startup founder, ex-Uber, and ex-Google. Now, he is building a healthcare AI startup in stealth mode; he joins us to talk about the enablers and obstacles in the current AI startup ecosystem. Andrii shares his views on the following challenges for organizations applying LLMs, such as converting bytes into high-quality data, ensuring the safety of LLMs, the implications of legal regulations on innovations, and expanding AI applicability to broader and more complex problems. Despite all the hurdles, Andrii sees AI as a great equalizer that will make many services more accessible and significantly enhance their speed and quality in numerous industries yet to be disrupted.

Connect with Andrii:
Twitter - twitter.com/yasik
Linkedin - https://www.linkedin.com/in/yasinetsky/
substack - https://yasik.substack.com/

Tiankai Feng is Head of Data Strategy & Governance Services at Thoughtworks Europe. Tiankai joined us to discuss inclusivity in data teams, data work, and beyond. While it may sound vague and unclear, during the discussion, we actually tried to unfold what it really means. In essence, we emphasized empathy to understand what it takes to do data work and, conversely, what data teams need to understand from business stakeholders to deliver outcomes that truly matter.

Check out Tiankai's LinkedIn; he does a great job there!

Andrew Jones, principal engineer at GoCardless, is the author of the book "Driving Data Quality with Data Contracts." During this session, we talked a lot about what a data platform is, who data platform engineers are, what it takes to make a data platform reliable, and, most importantly, how Andrew and his team managed to build a reliable platform at GoCardless. Sure enough, we touched a little on data contracts, their implementation, and the possibility of vendors doing the same as Andrew's team did.

Andrew's LinkedIn - https://www.linkedin.com/in/andrewrhysjones/

Rui Falhas Santos - is the Manager of Data Analytics at one of the largest banks in the world. He joined us to discuss the AI applications they have implemented. The creativity and the use case are very captivating, as it is applied in one of the most regulated and legacy-bound industries. Rui is a hands-on manager with an extensive background in data. His data team helped build a solution that reads, on average, 300k articles a month to catch any alarming signals about their clients. Additionally, we discussed responsible AI from the decision-making side of model output and how data is collected for model processing.

Maya Mikhailov from ⁠Savvi AI⁠ joins us to discuss AI, startups, and the real-world delivery of value to enterprises. The pressing challenge for organizations today is that while the C-suite is both willing and financially prepared to invest in AI strategies, there remains a significant gap between effectively applying AI, extracting tangible value, and overcoming the perception of AI as a miraculous fix-all.

Connect with Maya - https://www.linkedin.com/in/mayam/

Eric and Jean-Georges Perrin are talking about their upcoming book Implementing Data Mesh, but also about actually executing Data Mesh through an open-source project. 

Sayle Matthews leads the North American GCP Data Practice at DoiT International. Over the past year and a half, he has focused almost exclusively on BigQuery, helping hundreds of GCP customers optimize their usage and solve some of their biggest 'Big Data' challenges. With extensive experience in Google BigQuery billing, we sat down to discuss the changes and, most importantly, the impact these changes have had on the market, as observed by Sayle while working with hundreds of clients of various sizes at DoiT.

Sayle's LinkedIn page - https://www.linkedin.com/in/sayle-matthews-522a795/

Daniil Shvets, CEO and co-founder of ASAO DS: Data & AI Consulting Boutique, previously led various companies' Data Science and Product teams. Daniil sat down with Yuliia and Scott to share his opinion on Data Science being a business department with appropriate data skills rather than an IT department. He explained why having 54 ML models in one of the largest retailers in the USA is the wrong approach. Daniil also shared his views on the biggest challenges in perceiving Data Science's role. We also touched on AI and the consultancy business while Scott made all possible relationship analogies. :)

Daniil's Linkedin: https://www.linkedin.com/in/daniilshvets/

Jean-Georges Perrin is a serial startup founder, currently co-founder of AbeaData [https://abeadata.com/], and co-author of "Implementing Data Mesh." He is the one who championed the PayPal's data contract project, which is now part of Bitol and the Linux Foundation. In this episode, JGP speaks about building and maintaining open-source data contract solutions using open standards. He shares a lot about why and how he came to it and the challenges of maintaining it to avoid appropriation of the solution. JGP discusses how they balance the interests of different groups in developing a community around open data contract standards. More importantly, he shares how data contracts can positively change the life of every data engineer.

Check out JGP's LinkedIn
Check out Bitol -  Open Standards for Data Contracts and become a contributor.

Michael Toland is a Product Management Consultant and blog contributor with ⁠Test Double⁠, residing in Columbus, OH. His experience spans 8 formal years of internal Product Management, with a few additional years of doing Product Management without even knowing what the field really was.

In this episode, Michael shared how a data empowered company the size of Verizon was able to drastically reduce time-to-market metrics, experiment, and run data product MVPs in production. The reference data became a cornerstone of Verizon's go-to-market strategy and a glue for different teams and departments.

One of the key takeaways is that to deliver value with data products and architect them effectively, one does not need to be a data wizard but rather have a passion for solving problems.

Michael is also the author of an infrequently updated product satire site, ⁠Dignified Product.⁠

John Grubb is the Sr. Director of FinOps and Cost Modeling at Platform.sh. With experience as a former Data Platform Director, Director of BI & Analytics, and Director of Customer Care, John brings a sharp perspective on why cloud costs matter. He knows how to align financial and engineering teams and believes that FinOps is about maximizing the value of every cloud dollar rather than just cutting costs.
Follow John on Linkedin- https://www.linkedin.com/in/johnnygrubb/
John's blog - https://www.thefinoperator.com/

Scott Hirleman, founder of Data Mesh Radio, has a very diverse career, including a role as FinOps Manager. In this podcast, we sit down together to discuss his FinOps philosophy: cost containment, cost attribution, and cost forecasting. It's an insightful conversation on how to balance costs for data teams with both data and business considerations in mind.