Data: Heaven or Hell? (Adastra Podcast)

87: "Where Not to Use AI Matters More Than Where to Use It,” Says Brad Freels, Microsoft

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…

81: “The technology is good enough. The real hurdle now is people, fear, and change management,” says Shannon Bell, CIO, OpenText

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…

84: "Start with Business Challenges, Not Solutions," Says Justin Rister, Microsoft

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…

86: "31,000 customers have adopted Fabric in the last two and a half years," says Tamer Farag, Microsoft

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…

82: Risk in AI-Developed Cancer Drugs with Jon Steffey, Tolmar

83: AI není zkratka k lepšímu reportingu. Je to spíš test připravenosti vašich dat, říká Kristýna Merňáková (Adastra)

Jak připravit data, tak aby 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…

80: "Helpful, not creepy: personalization that earns trust," says Kevin McCurdy, Global CPG Partner Lead, AWS

Kevin McCurdy, Global Partner Lead, Consumer Goods, AWS, shows how Gen AI, trusted data, and risk-based guardrails turn experiments into repeatable CPG value. He highlights AWS and partner…

79: “Good enough to start, governed enough to scale," says Rehan Shah, AWS

Rehan Shah, General Manager and Head of Channel and Partner Sales for US Greenfield at AWS, explains how the right mix of AI tools, trustworthy data, and strong controls turns early AI trials into…

77: “Think of it as a three-layer cake: platform, data, AI,” says Glenn Remoreras, CIO, Breakthru Beverage Group

Glenn Remoreras, EVP, Chief Information Officer at Breakthru Beverage Group, shares how a cloud-first “platform, data, AI” architecture and executive-led AI readiness turn market pressures into…

78: "The car is becoming a smartphone on wheels, an extension of your living room," says Chris-Markus Kratz, AWS Global Director of Automotive and Manufacturing

Chris‑Markus “CMK” Kratz, AWS Global Director of Automotive and Manufacturing, explains how outcome‑first, customer‑obsessed transformation and ecosystem partnerships are reshaping the industry. He…

76: Data pomáhají lidem z dluhů. Digitalizace mění práci dluhových poraden (David Borges, Člověk v tísni)

Jak dlouho trval vývoj a rollout řešení?  Proč byl pilot klíčový pro přijetí mezi poradci?  A jaké další procesy chtějí v Člověku v tísni digitalizovat dál – od komunikace s finančním arbitrem až po…

82: AI makes no sense without customer impact. Implementing it just for the sake of technology is a dead end (Jan Vacek, DHL)

How do you set up an AI strategy in a large organization?  Why is security more important than speed?  And how do you prevent AI from turning into an uncontrolled “agent zoo”?

75: "It’s not about replacing people—it’s about empowering people," says Kevin Harmer, Chief Cloud Officer at Adastra

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74: Don’t wait for perfect data—start, then improve (Sam Wong, Mark Anthony Group)

What does it take to build an incubator that learns fast and delivers real value?   When is “good enough” data enough—and how can AI expose and improve the gaps?   Which operating model and…

73: Gorillas with Digital Wallets: How AI Helps Understand the Needs of Other Species (Jonathan Ledgard, Tehanu)

How can artificial intelligence help protect biodiversity? Will we ever objectively understand what is in the “interest” of other species? And what happens when the interests of different species…

71: The Future of Data Platforms? SaaS and AI, says Adam Wojtkowski from Snowflake

How does Snowflake work with AI models to keep data in a secure environment Why is going back to on-prem solutions no longer an option? And why does Wojtkowski believe SaaS and AI will dominate the…

72: Fabric unifies data work: one version for reporting, SQL, and AI (Lars Andersen, Microsoft)

What use cases are companies solving with Fabric most often? How can organizations start with smaller projects and scale them to an enterprise level? And why does Andersen believe it’s always worth…

70: AI-Ready Data Starts with Observability, Not Governance, says Elton Martins, former data leader at the NFL and Genius Sports

How can data observability organizations detect silent failures before they impact business decisions?  What’s the difference between data quality management and data observability—and why does it…

69: Bez dat AI neporadí. Odvaha začít něco nového je na lidech, říká Vladimír Bezděk, poradce českého prezidenta a šéf AVANT investiční společnost

Proč je porovnávání statutů fondů ideální úkol pro umělou inteligenci— a jak AVANTu pomáhá snížit riziko chyb i právní nejistoty. Jak by AI mohla asistovat při oceňování aktiv na základě předchozích…

68: Thanks to data governance, our analysts spend 50% less time on analysis, Says Pavlína Vajgarová from Česká spořitelna

How do you measure the success of data governance? Where do you find both the technical and “human” profiles for the team? And why should data governance be a natural part of work — not just another…