talk-data.com talk-data.com

Event

Straight Data Talk

2024-05-13 – 2025-11-24 Podcasts Visit website ↗

Activities tracked

3

Data’s messy, and we don’t sugarcoat it. We dig into real-world stories—FinOps, data platforms, streaming, governance—with people who’ve been there, screwed up, figured it out, and can still laugh about it. No buzzwords, no corporate cheerleading—just curious questions, practical insights, and the occasional bad joke.

Filtering by: LLM ×

Sessions & talks

Showing 1–3 of 3 · Newest first

Search within this event →

Ryan Dolley: The Modern Data Stack Bundling Era

2025-10-20 Listen
podcast_episode
Ryan Dolley , Yuliia Tkachova (Masthead Data) , Dumky de Wilde (Xebia Data)

Ryan Dolley, VP of Product Strategy at GoodData and co-host of Super Data Brothers podcast, joined Yuliia and Dumke to discuss the DBT-Fivetran merger and what it signals about the modern data stack's consolidation phase. After 16 years in BI and analytics, Ryan explains why BI adoption has been stuck at 27% for a decade and why simply adding AI chatbots won't solve it. He argues that at large enterprises, purchasing new software is actually the only viable opportunity to change company culture - not because of the features, but because it forces operational pauses and new ways of working. Ryan shares his take that AI will struggle with BI because LLMs are trained to give emotionally satisfying answers rather than accurate ones. Ryan Dolley linkedin

Patrick Thompson: From Data Quality to Decision Quality - Building Structured Systems in an AI-First World

2025-06-02 Listen
podcast_episode
Dumky , Patrick Thompson (Iteratively) , Yuliia Tkachova (Masthead Data)

Patrick Thompson, co-founder of Clarify and former co-founder of Iteratively (acquired by Amplitude), joined Yuliia and Dumky to discuss the evolution from data quality to decision quality. Patrick shares his experience building data contracts solutions at Atlassian and later developing analytics tracking tools. Patrick challenges the assumption that AI will eliminate the need for structured data. He argues that while LLMs excel at understanding unstructured data, businesses still need deterministic systems for automation and decision-making. Patrick shares insights on why enforcing data quality at the source remains critical, even in an AI-first world, and explains his shift from analytics to CRM while maintaining focus on customer data unification and business impact over technical perfectionism.Tune in!

Andrii Yasinetsky: AI as a Great Equalizer, yet to face many challenges

2024-05-27 Listen
podcast_episode

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/yasikLinkedin - https://www.linkedin.com/in/yasinetsky/substack - https://yasik.substack.com/