Couverture de Data: Heaven or Hell? (Adastra Podcast)

Data: Heaven or Hell? (Adastra Podcast)

Data: Heaven or Hell? (Adastra Podcast)

De : Adastra
Écouter gratuitement

À propos de ce contenu audio

 Listen to Adastra’s podcast dedicated to latest trends in data management, AI and analytics.

This engaging podcast series showcases the visionaries reshaping the tech landscape. Featuring strategic leaders and boardroom heroes who persuade decision-makers to back new technologies, each episode dives into stories of ambition, innovation, and collaboration.

Join us to witness the evolution of technology across various sectors.Adastra s.r.o. Economie Management Management et direction Politique et gouvernement
Épisodes
  • 82: Risk in AI-Developed Cancer Drugs with Jon Steffey, Tolmar

    82: Risk in AI-Developed Cancer Drugs with Jon Steffey, Tolmar
    Apr 16 2026
    21 min
  • 83: AI není zkratka k lepšímu reportingu. Je to spíš test připravenosti vašich dat, říká Kristýna Merňáková (Adastra)

    83: AI není zkratka k lepšímu reportingu. Je to spíš test připravenosti vašich dat, říká Kristýna Merňáková (Adastra)
    Apr 13 2026

    • 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 Power BI.
    Afficher plus Afficher moins
    44 min
  • 80: "Helpful, not creepy: personalization that earns trust," says Kevin McCurdy, Global CPG Partner Lead, AWS

    80: "Helpful, not creepy: personalization that earns trust," says Kevin McCurdy, Global CPG Partner Lead, AWS
    Mar 10 2026

    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 capabilities (Amazon Bedrock, SageMaker, secure integrations) with real wins such as demand forecasting, planogram automation, and Adastra’s Mark Anthony Group solution that scales assortment optimization and auto-generates seller scripts, plus quick-win assistants, cost controls, and an enterprise AI program with clear budgets, ownership, and accountability across product, employee, and customer use cases.

    • What does it take to move from quick wins with Amazon Q to custom, domain-aware agents on Bedrock that scale across the enterprise?
    • When is “good enough” data enough to start, and how can AI assistants surface gaps while improving data quality over time?
    • Which operating model and risk-based guardrails help leaders control cost and compliance while accelerating adoption?
    Afficher plus Afficher moins
    25 min
Aucun commentaire pour le moment