Data Dialogues (Middle East Edition) - Beyond the Lakehouse

Many organizations have invested millions in modern data lakehouses, but that’s not enough for the era of agentic AI. And 68% of public sector leaders struggle to optimize performance for AI workloads. In this Data Dialogues (Middle East Edition) episode, Hazem Abu Nameh, Data & AI Expert at Denodo, explains why the lakehouse alone can’t power agentic AI. Agentic AI needs a bridge to live operational systems, while many architectures still rely on static pools of historical data, and consolidating everything in one place creates a bottleneck. The answer isn’t to replace the lakehouse, but to supplement it with logical data management. The lakehouse works as deep memory for training models, while a logical layer acts as a nervous system that connects AI directly to live databases and SaaS platforms. Denodo’s hybrid approach combines the power of central storage with agile, virtual, real-time access. In this video you’ll learn: - Why modern data lakehouses fall short for agentic AI - How a logical data layer works as the “nervous system” alongside the lakehouse’s “deep memory” - How a hybrid approach optimizes cost, improves performance and speeds up return on investment Is your data architecture an enabler for AI, or a bottleneck? Source for the 68% statistic: Denodo, The AI Trust Gap in the Public Sector (https://okt.to/ds9IjK). 👉 See how Denodo works alongside your lakehouse to deliver live, governed data to AI: https://okt.to/H2d3hy ⏱️ Chapters 0:00 Why the lakehouse isn’t enough for agentic AI 0:33 The bottleneck: static data vs live operational systems 0:47 Supplement, don’t replace: deep memory and nervous system 1:10 Denodo’s hybrid approach: central storage meets real-time access 1:23 Three benefits: cost, performance, faster ROI 1:56 Beyond the lakehouse: bottleneck or enabler? #DataDialogues #AgenticAI #DataLakehouse #LogicalDataManagement #AIDataLayer #DataArchitecture #PublicSector #DataforALL