YouTube ADASTRA

České školství se nedá změnit jedním rozhodnutím shora. Podle Tomáše Kaplana z Nadačního fondu Eduzměna je potřeba pracovat přímo v regionech, se školami, řediteli, učiteli, rodiči i zřizovateli. A právě proto začínají hrát zásadní roli data a AI. „Bez pomoci AI nebo moderních technologií si s tím už moc nevíme rady. Museli bychom mít mnohem větší tým,“ říká v novém dílu podcastu Adastry.

6. 7. 2026

In diesem Vortrag spricht Dr. Patrick Bartsch, Principal Evangelist Automotive bei AWS, über die Anforderungen der Industrie im Bereich Künstliche Intelligenz und darüber, wie Unternehmen mit AWS-Services eigene KI-basierte Anwendungen entwickeln können. Im Fokus steht das Thema Smart Production mit Souveränität: Wie lassen sich moderne KI-Technologien sinnvoll, sicher und praxisnah in industriellen Umgebungen einsetzen? Der Vortrag gibt Einblicke in aktuelle Herausforderungen, mögliche Lösungsansätze und die Rolle von Cloud- und KI-Services für die Produktion der Zukunft.

17. 6. 2026

Chris Peart, Sales Leader at Snowflake Canada, shares how unified data, governed context, and agentic AI are reshaping how enterprises turn information into action. He explains why "context is king" as frontier models become commoditized, how a single AI Data Cloud across AWS, Azure, and GCP removes the brittleness of traditional architectures, and how Snowflake Cortex and Coworker give knowledge workers immediate answers instead of waiting weeks for engineering teams. He also digs into the agentic future and the cultural shift required to win with AI: why "nobody sells anybody anything" and customers buy outcomes, why Canadian enterprises are falling behind global peers by being too cautious, and how the next frontier is autonomous agents negotiating with other agents across organizational boundaries. The episode answers: • Why is your data, not the model you choose, the true competitive differentiator in the agentic era? • What does a governed context layer look like, and why is it the foundation for agents you can trust? • Why are Canadian enterprises falling behind global peers on AI, and what does it take to start swinging?

29. 6. 2026

Justin Rister, Senior Cloud and AI Specialist at Microsoft, explains why leaders should start with business pain points, not technology. He shares how Fabric unifies the analytics stack for teams of all skillsets, why Databricks and Fabric are a better-together story, and how an AI layer on unified data empowers business users to ask questions and get answers without waiting on IT. What does it mean to be a strategic partner instead of a product pusher? How do you remove bottlenecks by letting business users access insights directly? Why should leaders think big, start small, and scale fast?

21. 5. 2026

Brad Freels, Azure Data and AI Specialist at Microsoft, shares how meeting customers where they are, building AI Centers of Excellence, and diving in without waiting for "perfect data" are reshaping how enterprises unlock value from cloud, data, and AI. He explains why the biggest barrier to AI isn't technology but fear and paralysis, how partners compress time to value by bridging Microsoft best practices to each customer's unique environment, and why executive-sponsored Centers of Excellence lower the temperature on change management while creating guardrails that prevent shadow AI and governance nightmares. He also shows where to start now, such as standing up a 60-day Fabric trial, rebuilding an existing report, and letting AI itself help curate the messy data you already have, because your competitors aren't waiting and neither should you.  • What does it really take to move from fear of AI to a culture that leans into it?   • How can you start small with the data and tools you already have and still build toward enterprise-wide transformation?   • Which guardrails, sponsorship, and partner relationships let you accelerate AI adoption without losing control? 

29. 6. 2026

Brandon Ash, Director of Solution Engineering at Microsoft, shares how enterprise leaders can navigate the AI era by building governed, unified data foundations. He explains why the semantic layer is more critical than ever, how OneLake enables a "skunkworks with guardrails" approach, and why customers who embrace partners go further, faster.  This podcast will answer:  • What's holding executives back from AI, and how does semantic debt compound the problem?  • How does Fabric bridge the gap between analytics and operational decision-making?  • Why should you think of AI agents as just another employee to onboard? 

29. 6. 2026

Justin Rister, Senior Cloud and AI Specialist at Microsoft, explains why leaders should start with business pain points, not technology. He shares how Fabric unifies the analytics stack for teams of all skillsets, why Databricks and Fabric are a better-together story, and how an AI layer on unified data empowers business users to ask questions and get answers without waiting on IT.  • What does it mean to be a strategic partner instead of a product pusher?   • How do you remove bottlenecks by letting business users access insights directly?  • Why should leaders think big, start small, and scale fast? 

29. 6. 2026

Tamer Farag, Global Fabric Partner Lead at Microsoft, shares how the fastest-growing analytics platform in the world is helping 31,000 customers unify fragmented data estates and unlock AI value. He highlights why you don't need to move your data to govern it, how mirroring is offered free to accelerate adoption, and what makes partners like Adastra critical to scaling Fabric globally.  • What does it take to connect AI to your data without a massive migration project?   • How is Fabric enabling customers to move from static reports to asking questions directly to their data?  • Which trends, from real-time intelligence to chat with your data, are driving customer demand in 2026? 

29. 6. 2026

Tamer Farag, Global Fabric Partner Lead at Microsoft, shares how the fastest-growing analytics platform in the world is helping 31,000 customers unify fragmented data estates and unlock AI value. He highlights why you don't need to move your data to govern it, how mirroring is offered free to accelerate adoption, and what makes partners like Adastra critical to scaling Fabric globally. What does it take to connect AI to your data without a massive migration project? How is Fabric enabling customers to move from static reports to asking questions directly to their data? Which trends, from real-time intelligence to chat with your data, are driving customer demand in 2026?

28. 4. 2026

Jon Steffey, Senior Director of Enterprise Software and Analytics at Tolmar, shares how a unified data platform, risk‑aware governance, and AI‑enabled workflows are helping a mid‑sized pharma manufacturer modernize without losing sight of quality. He explains how Tolmar is digitizing manual processes, breaking down post‑M&A data silos, and using Microsoft Fabric to move leaders from data overload and gut feel to more empirical decisions. Drawing on experience in aerospace, medical devices, and pharma, he shows why data is foundational to process control in regulated manufacturing and how to match the rigor of controls to real product and patient risk. How do you modernize a legacy, siloed pharma data landscape while focusing on fundamentals like ingestion, transformation, and governance instead of chasing a single “killer” use case? What changes when leaders move from fragmented reports to a unified view of end‑to‑end manufacturing and quality data? How can pharma organizations tune development and validation rigor to the impact and risk of each use case, from low‑risk UI changes to high‑impact, AI‑influenced therapies?

20. 4. 2026

29. 6. 2026

• Jak připravit data, tak aby AI (https://adastracorp.com/cs/adastra-ai/) skutečně pomáhala a neškodila?  • Jak funguje „chat with your data“ v praxi?  • A proč bez kontextu AI odpovídá špatně, i když má správná data? Zjistěte více o řešení Power BI (https://adastracorp.com/cs/power-bi/) .

13. 4. 2026

AI v reportingu nepřináší jen zrychlení. Velmi rychle také odhalí slabiny: špatně definované metriky, nejasné pojmy nebo chybějící kontext. A právě to je dnes pro mnoho organizací větší problém než samotná technologie. Podcast Adastry.

12. 4. 2026

Shannon Bell, EVP, Chief Digital Officer and Chief Information Officer at OpenText, shares how “information first” thinking, simplicity, and agentic AI are reshaping how large enterprises work. She explains why most enterprises don’t have an AI problem but an information problem, how to go slow to go fast with AI, and how a blended workforce of humans and AI agents turns scarce skills and fragmented processes into scalable value.  Crucially, she digs into change management and the future of jobs: why fear of displacement is often higher than the reality, how to position AI as a copilot rather than a competitor, and what it means to give 22,000+ employees an AI development goal so they can actively shape how their roles evolve. She also shows where agentic AI is ready now, such as search and summarize, root cause analysis, and software delivery, and why success depends on clear roles, governed data, and using HR and SRE teams as early champions to build an “AI fabric” across the enterprise.  • What does it really take to make AI an assistant, not a threat, for your workforce?  • How can you start small on messy, real-world systems and still build toward an AI ready data estate?  • Which foundations, guardrails, and operating model let you decentralize AI innovation without losing control?  

13. 4. 2026

In under two months, Tolmar unified data from a dozen systems into Microsoft Fabric and built production-ready, cross-domain insights across manufacturing, quality, and inventory. With Adastra’s metadata-driven ingestion, AI-accelerated Data 360, and a Fabric data agent, business users now ask natural language questions on governed data, eliminating Excel stitching, accelerating decisions, and proactively protecting patient supply and outcomes.

24. 3. 2026