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​In this podcast episode, we’ll be joined by Sofya Yulpatova, Founder and CEO of a PetTech startup building what many describe as an early version of the “Apple Watch for dogs.” Her work sits at the intersection of machine learning, sensor data, and real-world behaviour patterns, and she brings a refreshingly honest view of what it takes to make pet health measurable.

​We'll discuss the challenges in animal health technology compared to human wearables, such as dogs' unpredictable behavior and the difficulty of collecting useful data. Sofya will explain why many early health signals are often undetectable by owners but clear in the data. ​We’ll also cover the technical side, including developing models for different dog breeds, managing sensor noise, and creating feedback loops with veterinarians and pet owners.

​Topics we plan to explore:

• ​Why sleep patterns may be the strongest and most overlooked health indicator
• ​How small daily behaviour changes can reveal early discomfort
• ​The realities of collecting embedded sensor data in the real world
• ​Challenges around calorie estimation, device variability, and multi-dog generalization
• ​Lessons from early prototypes and testing with real pets

​This episode explores how machine learning, sensor data, and behavioral science intersect, demonstrating how applied machine learning can advance pet health technology to meet expectations similar to those of human wearables. ​

​About the Speaker:

​Sofya Yulpatova is the Founder and CEO of Fit Tails, a PetTech startup developing an activity and health tracker for pets. She has a background in computer science, machine learning, and product management, and previously managed product and delivery operations at FixParts, an international automotive parts distributor. Sofya studied at the University of Latvia and completed the Sales and Marketing Programme at the Stockholm School of Economics in Riga.

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The Inside Economics crew welcomes Alan Blinder back to the podcast. The Princeton University economics professor and former Vice Chair of the Fed offers his perspective on the outlook for artificial intelligence, the risk of a bubble in equity markets, and the potential implications of current threats to Fed independence. The team also breaks down the much-delayed September employment report. Guest: Alan Blinder – Professor of Economics and Public Affairs at Princeton University Get more information on Alan Blinder's book - A Monetary and Fiscal History of the United States, 1961-2021 Hosts: Mark Zandi – Chief Economist, Moody’s Analytics, Cris deRitis – Deputy Chief Economist, Moody’s Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody’s Analytics Follow Mark Zandi on 'X' and BlueSky @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn

Questions or Comments, please email us at [email protected]. We would love to hear from you.    To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.

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¿Y si la inversión más rentable de tu vida… no estuviera en un banco, ni en un fondo, ni en la bolsa? 💡¿Nos creerías?

En este episodio hablamos con Rosanna Ruiz (Presidenta de la Asociación de Bancos Múltiples (ABA) sí, la #MamáDeLaura sobre algo que te cambia la vida (y el bolsillo): 💡 invertir en TI. Si quieres crecer en tu carrera, ganar más, emprender o simplemente ser tu mejor versión… este episodio es para ti.

Además, compartimos un código especial exclusivo para nuestra comunidad: EDUCACION.ECONOMICS

Dale ME GUSTA 👍 a este video y COMENTA  💬 ¿en qué estás pensando invertir en este último mes del año?

🔔 Suscríbete y activa la campana para más episodios que te ayudan a crecer

The Inside Economics team records a rare Saturday podcast. They consider the fallout from the just-ended government shutdown on the broader economy and the economic data.  It’s not good, but it ended just before it did serious damage. The team also takes up the Trump administration’s pivot to addressing affordability, including scaling back tariffs, most important for the group, those on pasta and bananas.  And they introduce a new regular segment of the podcast – listener questions.  So, keep them coming. Hosts: Mark Zandi – Chief Economist, Moody’s Analytics, Cris deRitis – Deputy Chief Economist, Moody’s Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody’s Analytics Follow Mark Zandi on 'X' and BlueSky @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn

Questions or Comments, please email us at [email protected]. We would love to hear from you.    To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.

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Summary In this episode Kate Shaw, Senior Product Manager for Data and SLIM at SnapLogic, talks about the hidden and compounding costs of maintaining legacy systems—and practical strategies for modernization. She unpacks how “legacy” is less about age and more about when a system becomes a risk: blocking innovation, consuming excess IT time, and creating opportunity costs. Kate explores technical debt, vendor lock-in, lost context from employee turnover, and the slippery notion of “if it ain’t broke,” especially when data correctness and lineage are unclear. Shee digs into governance, observability, and data quality as foundations for trustworthy analytics and AI, and why exit strategies for system retirement should be planned from day one. The discussion covers composable architectures to avoid monoliths and big-bang migrations, how to bridge valuable systems into AI initiatives without lock-in, and why clear success criteria matter for AI projects. Kate shares lessons from the field on discovery, documentation gaps, parallel run strategies, and using integration as the connective tissue to unlock data for modern, cloud-native and AI-enabled use cases. She closes with guidance on planning migrations, defining measurable outcomes, ensuring lineage and compliance, and building for swap-ability so teams can evolve systems incrementally instead of living with a “bowl of spaghetti.”

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data managementData teams everywhere face the same problem: they're forcing ML models, streaming data, and real-time processing through orchestration tools built for simple ETL. The result? Inflexible infrastructure that can't adapt to different workloads. That's why Cash App and Cisco rely on Prefect. Cash App's fraud detection team got what they needed - flexible compute options, isolated environments for custom packages, and seamless data exchange between workflows. Each model runs on the right infrastructure, whether that's high-memory machines or distributed compute. Orchestration is the foundation that determines whether your data team ships or struggles. ETL, ML model training, AI Engineering, Streaming - Prefect runs it all from ingestion to activation in one platform. Whoop and 1Password also trust Prefect for their data operations. If these industry leaders use Prefect for critical workflows, see what it can do for you at dataengineeringpodcast.com/prefect.Data migrations are brutal. They drag on for months—sometimes years—burning through resources and crushing team morale. Datafold's AI-powered Migration Agent changes all that. Their unique combination of AI code translation and automated data validation has helped companies complete migrations up to 10 times faster than manual approaches. And they're so confident in their solution, they'll actually guarantee your timeline in writing. Ready to turn your year-long migration into weeks? Visit dataengineeringpodcast.com/datafold today for the details.Your host is Tobias Macey and today I'm interviewing Kate Shaw about the true costs of maintaining legacy systemsInterview IntroductionHow did you get involved in the area of data management?What are your crtieria for when a given system or service transitions to being "legacy"?In order for any service to survive long enough to become "legacy" it must be serving its purpose and providing value. What are the common factors that prompt teams to deprecate or migrate systems?What are the sources of monetary cost related to maintaining legacy systems while they remain operational?Beyond monetary cost, economics also have a concept of "opportunity cost". What are some of the ways that manifests in data teams who are maintaining or migrating from legacy systems?How does that loss of productivity impact the broader organization?How does the process of migration contribute to issues around data accuracy, reliability, etc. as well as contributing to potential compromises of security and compliance?Once a system has been replaced, it needs to be retired. What are some of the costs associated with removing a system from service?What are the most interesting, innovative, or unexpected ways that you have seen teams address the costs of legacy systems and their retirement?What are the most interesting, unexpected, or challenging lessons that you have learned while working on legacy systems migration?When is deprecation/migration the wrong choice?How have evolutionary architecture patterns helped to mitigate the costs of system retirement?Contact Info LinkedInParting Question From your perspective, what is the biggest gap in the tooling or technology for data management today?Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being used. The AI Engineering Podcast is your guide to the fast-moving world of building AI systems.Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.If you've learned something or tried out a project from the show then tell us about it! Email [email protected] with your story.Links SnapLogicSLIM == SnapLogic Intelligent ModernizerOpportunity CostSunk Cost FallacyData GovernanceEvolutionary ArchitectureThe intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

The Inside Economics team welcomes Lisa Simon, Chief Economist at Revelio Labs, for an unusual jobs Friday podcast as the ongoing government shutdown prevented the release of the September employment report. Lisa details the new public labor statistics data that Revelio Labs began publishing recently in the wake of turmoil at the Bureau of Labor Statistics. The team discusses how private data sources can help fill in the gaps left by the temporary absence of government data and also dissects the current state of the labor market. Guest: Lisa Simon – Chief Economics, Revelio Labs For more about Lisa Simon, click here: https://www.reveliolabs.com/author/lisa-k-simon/ Explore the risks and realities shaping the economy in our new webinar, now streaming for free. U.S. Economic Outlook: Under Unprecedented Uncertainty Watch here: https://events.moodys.com/mc68453-wbn-2025-mau25777-us-macro-outlook-precipice-recession?mkt_tok=OT… Hosts: Mark Zandi – Chief Economist, Moody’s Analytics, Cris deRitis – Deputy Chief Economist, Moody’s Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody’s Analytics

Questions or Comments, please email us at [email protected]. We would love to hear from you.    To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.

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En este episodio hablamos de uno de los gastos principales de todo hogar: el supermercado 🛒 y cómo hemos tenido que revolucionar el manejo de este gasto en nuestras casas, porque sí puedes ahorrar sin dejar de comer. 😩💸 #economicsdata #supermercado #gasto ¡ Suscríbete y activa la campana  🔔 de notificaciones! 👍 Comparte este episodio si te ayudó en algo 📲

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The Inside Economics team gets together in person at All Hands Day. It is a short podcast, with more than the typical amount of chit-chat (as we are in person). But it is an action-packed conversation on the Fed’s rate decision (see if we got it right), our proposal to unlock the housing market, and, of course, the statistics game! Explore the risks and realities shaping the economy in our new webinar, now streaming for free: U.S. Economic Outlook: Under Unprecedented Uncertainty Watch here: https://events.moodys.com/mc68453-wbn-2025-mau25777-us-macro-outlook-precipice-recession?mkt_tok=OT… Hosts: Mark Zandi – Chief Economist, Moody’s Analytics, Cris deRitis – Deputy Chief Economist, Moody’s Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody’s Analytics Follow Mark Zandi on 'X' and BlueSky @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn Questions or Comments, please email us at [email protected]. We would love to hear from you. 

Questions or Comments, please email us at [email protected]. We would love to hear from you.    To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.